From 8766f807251763a49b21cfa944b1980f31b5902a Mon Sep 17 00:00:00 2001 From: Snehal Mankar Date: Mon, 4 Sep 2023 21:10:49 +0530 Subject: [PATCH] Day 49 commit - Capstone Prof - 5G Resource Allocation: MLR, SVR, KNN_R --- ...of-service-all-regression-algorithms.ipynb | 1 + ...y-of-service-all-regression-algorithms.pdf | Bin 0 -> 1195131 bytes 2 files changed, 1 insertion(+) create mode 100644 49. Day 49 - Capstone Project - 5G Resources - MLR, SVR, KNN_R/5g-quality-of-service-all-regression-algorithms.ipynb create mode 100644 49. Day 49 - Capstone Project - 5G Resources - MLR, SVR, KNN_R/5g-quality-of-service-all-regression-algorithms.pdf diff --git a/49. Day 49 - Capstone Project - 5G Resources - MLR, SVR, KNN_R/5g-quality-of-service-all-regression-algorithms.ipynb b/49. Day 49 - Capstone Project - 5G Resources - MLR, SVR, KNN_R/5g-quality-of-service-all-regression-algorithms.ipynb new file mode 100644 index 0000000..929de16 --- /dev/null +++ b/49. Day 49 - Capstone Project - 5G Resources - MLR, SVR, KNN_R/5g-quality-of-service-all-regression-algorithms.ipynb @@ -0,0 +1 @@ +{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# **Resource Allocation in 5G Network Service**","metadata":{}},{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.121288Z","iopub.execute_input":"2023-09-04T15:17:55.121704Z","iopub.status.idle":"2023-09-04T15:17:55.127761Z","shell.execute_reply.started":"2023-09-04T15:17:55.121675Z","shell.execute_reply":"2023-09-04T15:17:55.126583Z"},"trusted":true},"execution_count":191,"outputs":[]},{"cell_type":"code","source":"df = pd.read_csv('/kaggle/input/5g-quality-of-service/Quality of Service 5G.csv')","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.200949Z","iopub.execute_input":"2023-09-04T15:17:55.201364Z","iopub.status.idle":"2023-09-04T15:17:55.223818Z","shell.execute_reply.started":"2023-09-04T15:17:55.201330Z","shell.execute_reply":"2023-09-04T15:17:55.222914Z"},"trusted":true},"execution_count":192,"outputs":[]},{"cell_type":"code","source":"df","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.360365Z","iopub.execute_input":"2023-09-04T15:17:55.361619Z","iopub.status.idle":"2023-09-04T15:17:55.379111Z","shell.execute_reply.started":"2023-09-04T15:17:55.361582Z","shell.execute_reply":"2023-09-04T15:17:55.377797Z"},"trusted":true},"execution_count":193,"outputs":[{"execution_count":193,"output_type":"execute_result","data":{"text/plain":" Timestamp User_ID Application_Type Signal_Strength Latency \\\n0 9/3/2023 10:00 User_1 Video_Call -75 dBm 30 ms \n1 9/3/2023 10:00 User_2 Voice_Call -80 dBm 20 ms \n2 9/3/2023 10:00 User_3 Streaming -85 dBm 40 ms \n3 9/3/2023 10:00 User_4 Emergency_Service -70 dBm 10 ms \n4 9/3/2023 10:00 User_5 Online_Gaming -78 dBm 25 ms \n.. ... ... ... ... ... \n395 9/3/2023 10:06 User_396 Streaming -110 dBm 61 ms \n396 9/3/2023 10:06 User_397 Video_Call -40 dBm 53 ms \n397 9/3/2023 10:06 User_398 Video_Streaming -113 dBm 58 ms \n398 9/3/2023 10:06 User_399 Emergency_Service -40 dBm 5 ms \n399 9/3/2023 10:06 User_400 Web_Browsing -113 dBm 0 ms \n\n Required_Bandwidth Allocated_Bandwidth Resource_Allocation \n0 10 Mbps 15 Mbps 70% \n1 100 Kbps 120 Kbps 80% \n2 5 Mbps 6 Mbps 75% \n3 1 Mbps 1.5 Mbps 90% \n4 2 Mbps 3 Mbps 85% \n.. ... ... ... \n395 1.3 Mbps 1.8 Mbps 85% \n396 14.5 Mbps 15.8 Mbps 75% \n397 1.0 Mbps 1.4 Mbps 70% \n398 0.4 Mbps 0.4 Mbps 70% \n399 0.1 Mbps 0.1 Mbps 70% \n\n[400 rows x 8 columns]","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampUser_IDApplication_TypeSignal_StrengthLatencyRequired_BandwidthAllocated_BandwidthResource_Allocation
09/3/2023 10:00User_1Video_Call-75 dBm30 ms10 Mbps15 Mbps70%
19/3/2023 10:00User_2Voice_Call-80 dBm20 ms100 Kbps120 Kbps80%
29/3/2023 10:00User_3Streaming-85 dBm40 ms5 Mbps6 Mbps75%
39/3/2023 10:00User_4Emergency_Service-70 dBm10 ms1 Mbps1.5 Mbps90%
49/3/2023 10:00User_5Online_Gaming-78 dBm25 ms2 Mbps3 Mbps85%
...........................
3959/3/2023 10:06User_396Streaming-110 dBm61 ms1.3 Mbps1.8 Mbps85%
3969/3/2023 10:06User_397Video_Call-40 dBm53 ms14.5 Mbps15.8 Mbps75%
3979/3/2023 10:06User_398Video_Streaming-113 dBm58 ms1.0 Mbps1.4 Mbps70%
3989/3/2023 10:06User_399Emergency_Service-40 dBm5 ms0.4 Mbps0.4 Mbps70%
3999/3/2023 10:06User_400Web_Browsing-113 dBm0 ms0.1 Mbps0.1 Mbps70%
\n

400 rows × 8 columns

\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"> **1. Data Pre-Processing :**","metadata":{}},{"cell_type":"code","source":"# Get all insights from the DataFrame\ndf.info()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.520884Z","iopub.execute_input":"2023-09-04T15:17:55.521275Z","iopub.status.idle":"2023-09-04T15:17:55.533547Z","shell.execute_reply.started":"2023-09-04T15:17:55.521246Z","shell.execute_reply":"2023-09-04T15:17:55.532153Z"},"trusted":true},"execution_count":194,"outputs":[{"name":"stdout","text":"\nRangeIndex: 400 entries, 0 to 399\nData columns (total 8 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 Timestamp 400 non-null object\n 1 User_ID 400 non-null object\n 2 Application_Type 400 non-null object\n 3 Signal_Strength 400 non-null object\n 4 Latency 400 non-null object\n 5 Required_Bandwidth 400 non-null object\n 6 Allocated_Bandwidth 400 non-null object\n 7 Resource_Allocation 400 non-null object\ndtypes: object(8)\nmemory usage: 25.1+ KB\n","output_type":"stream"}]},{"cell_type":"code","source":"# Check for NULL Values\ndf.isna().sum()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.580542Z","iopub.execute_input":"2023-09-04T15:17:55.581669Z","iopub.status.idle":"2023-09-04T15:17:55.590531Z","shell.execute_reply.started":"2023-09-04T15:17:55.581630Z","shell.execute_reply":"2023-09-04T15:17:55.589393Z"},"trusted":true},"execution_count":195,"outputs":[{"execution_count":195,"output_type":"execute_result","data":{"text/plain":"Timestamp 0\nUser_ID 0\nApplication_Type 0\nSignal_Strength 0\nLatency 0\nRequired_Bandwidth 0\nAllocated_Bandwidth 0\nResource_Allocation 0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"# Check for Duplicates\ndf.duplicated().sum()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.655822Z","iopub.execute_input":"2023-09-04T15:17:55.656240Z","iopub.status.idle":"2023-09-04T15:17:55.665671Z","shell.execute_reply.started":"2023-09-04T15:17:55.656209Z","shell.execute_reply":"2023-09-04T15:17:55.664178Z"},"trusted":true},"execution_count":196,"outputs":[{"execution_count":196,"output_type":"execute_result","data":{"text/plain":"0"},"metadata":{}}]},{"cell_type":"code","source":"# Start with encoding df['Application_Type']\n\ndf['Application_Type'].unique()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.740610Z","iopub.execute_input":"2023-09-04T15:17:55.741010Z","iopub.status.idle":"2023-09-04T15:17:55.748804Z","shell.execute_reply.started":"2023-09-04T15:17:55.740980Z","shell.execute_reply":"2023-09-04T15:17:55.747549Z"},"trusted":true},"execution_count":197,"outputs":[{"execution_count":197,"output_type":"execute_result","data":{"text/plain":"array(['Video_Call', 'Voice_Call', 'Streaming', 'Emergency_Service',\n 'Online_Gaming', 'Background_Download', 'Web_Browsing',\n 'IoT_Temperature', 'Video_Streaming', 'File_Download', 'VoIP_Call'],\n dtype=object)"},"metadata":{}}]},{"cell_type":"markdown","source":"> **df['Application_Type']**\n\n* Contains the following unique values: ['Video_Call', 'Voice_Call', 'Streaming', 'Emergency_Service', 'Online_Gaming', 'Background_Download', 'Web_Browsing', 'IoT_Temperature', 'Video_Streaming', 'File_Download', 'VoIP_Call']\n\n* These all categories can be arranged in increasing Ordered form of Resource requirement: \n 1. IoT_Temperature\n 2. Web_Browsing\n 3. VoIP_Call \n 4. Video_Call\n 5. File_Download\n 6. Background_Download\n 7. Streaming \n 8. Video_Streaming\n 9. Online_Gaming\n 10. Emergency_Service\n\n* So, use Ordinal Encoding technique to transform the text data to numeric values.","metadata":{}},{"cell_type":"code","source":"from sklearn.preprocessing import OrdinalEncoder\n\n# Arrange data in ordered categories\ndata = [['IoT_Temperature', 'Web_Browsing', 'VoIP_Call', 'Voice_Call', 'Video_Call', 'File_Download',\n 'Background_Download', 'Streaming', 'Video_Streaming', 'Online_Gaming', 'Emergency_Service']]\n\nencoder = OrdinalEncoder(categories=data)\n\nprint(df['Application_Type'].unique())\ndf['Application_Type'] = encoder.fit_transform(np.array(df['Application_Type']).reshape(-1,1))\nprint(df['Application_Type'].unique())","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.780322Z","iopub.execute_input":"2023-09-04T15:17:55.780700Z","iopub.status.idle":"2023-09-04T15:17:55.791634Z","shell.execute_reply.started":"2023-09-04T15:17:55.780669Z","shell.execute_reply":"2023-09-04T15:17:55.790401Z"},"trusted":true},"execution_count":198,"outputs":[{"name":"stdout","text":"['Video_Call' 'Voice_Call' 'Streaming' 'Emergency_Service' 'Online_Gaming'\n 'Background_Download' 'Web_Browsing' 'IoT_Temperature' 'Video_Streaming'\n 'File_Download' 'VoIP_Call']\n[ 4. 3. 7. 10. 9. 6. 1. 0. 8. 5. 2.]\n","output_type":"stream"}]},{"cell_type":"code","source":"# Remove unwanted substr and convert df['Resource_Allocation'] to int dtype\n\ndf['Resource_Allocation'] = df['Resource_Allocation'].str.replace('%','').astype('int')","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.846386Z","iopub.execute_input":"2023-09-04T15:17:55.846823Z","iopub.status.idle":"2023-09-04T15:17:55.854492Z","shell.execute_reply.started":"2023-09-04T15:17:55.846777Z","shell.execute_reply":"2023-09-04T15:17:55.853109Z"},"trusted":true},"execution_count":199,"outputs":[]},{"cell_type":"code","source":"# Remove unwanted substr and convert df['User_ID'] to int dtype\n\ndf['User_ID'] = df['User_ID'].str.replace('User_','').astype('int')","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.930528Z","iopub.execute_input":"2023-09-04T15:17:55.930955Z","iopub.status.idle":"2023-09-04T15:17:55.938657Z","shell.execute_reply.started":"2023-09-04T15:17:55.930921Z","shell.execute_reply":"2023-09-04T15:17:55.937397Z"},"trusted":true},"execution_count":200,"outputs":[]},{"cell_type":"code","source":"# Bandwidth contains 2 units : Kbps and Mbps, where Kbps=1000*Mbps\n# Mbps : Convert to Kbps\n# Kbps : Leave as it is\n\ndef mbps_to_kbps(value): \n if 'Mbps' in value:\n n = float(value.replace(' Mbps',''))\n return str(n*1000)+' Kbps'\n else:\n return value\n\n\ndf['Required_Bandwidth'] = df['Required_Bandwidth'].map(mbps_to_kbps)\ndf['Allocated_Bandwidth'] = df['Allocated_Bandwidth'].map(mbps_to_kbps)\n","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:55.965507Z","iopub.execute_input":"2023-09-04T15:17:55.965947Z","iopub.status.idle":"2023-09-04T15:17:55.974992Z","shell.execute_reply.started":"2023-09-04T15:17:55.965909Z","shell.execute_reply":"2023-09-04T15:17:55.974031Z"},"trusted":true},"execution_count":201,"outputs":[]},{"cell_type":"code","source":"# Remove unwanted substr and convert df['Required_Bandwidth'] and \n# df['Allocated_Bandwidth'] to int dtype\n\ndf['Required_Bandwidth'] = df['Required_Bandwidth'].str.replace(' Kbps','').astype('float')\ndf['Allocated_Bandwidth'] = df['Allocated_Bandwidth'].str.replace(' Kbps','').astype('float')","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.025752Z","iopub.execute_input":"2023-09-04T15:17:56.026143Z","iopub.status.idle":"2023-09-04T15:17:56.034976Z","shell.execute_reply.started":"2023-09-04T15:17:56.026113Z","shell.execute_reply":"2023-09-04T15:17:56.033844Z"},"trusted":true},"execution_count":202,"outputs":[]},{"cell_type":"code","source":"# Remove unwanted substr and convert df['Latency'] to int dtype\ndf['Latency'] = df['Latency'].str.replace(' ms','').astype('int')","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.100617Z","iopub.execute_input":"2023-09-04T15:17:56.101035Z","iopub.status.idle":"2023-09-04T15:17:56.108414Z","shell.execute_reply.started":"2023-09-04T15:17:56.101003Z","shell.execute_reply":"2023-09-04T15:17:56.107235Z"},"trusted":true},"execution_count":203,"outputs":[]},{"cell_type":"code","source":"# Remove unwanted substr and convert df['Signal_Strength'] to int dtype\ndf['Signal_Strength'] = df['Signal_Strength'].str.replace(' dBm','').astype('int')","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.200559Z","iopub.execute_input":"2023-09-04T15:17:56.201228Z","iopub.status.idle":"2023-09-04T15:17:56.208515Z","shell.execute_reply.started":"2023-09-04T15:17:56.201188Z","shell.execute_reply":"2023-09-04T15:17:56.207304Z"},"trusted":true},"execution_count":204,"outputs":[]},{"cell_type":"code","source":"# Cast 'Timestamp' col dtype from object to datetime\ndf['Timestamp'] = pd.to_datetime(df['Timestamp'])","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.335596Z","iopub.execute_input":"2023-09-04T15:17:56.336029Z","iopub.status.idle":"2023-09-04T15:17:56.345427Z","shell.execute_reply.started":"2023-09-04T15:17:56.335994Z","shell.execute_reply":"2023-09-04T15:17:56.343753Z"},"trusted":true},"execution_count":205,"outputs":[]},{"cell_type":"code","source":"df.info()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.400458Z","iopub.execute_input":"2023-09-04T15:17:56.400881Z","iopub.status.idle":"2023-09-04T15:17:56.413962Z","shell.execute_reply.started":"2023-09-04T15:17:56.400845Z","shell.execute_reply":"2023-09-04T15:17:56.412797Z"},"trusted":true},"execution_count":206,"outputs":[{"name":"stdout","text":"\nRangeIndex: 400 entries, 0 to 399\nData columns (total 8 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 Timestamp 400 non-null datetime64[ns]\n 1 User_ID 400 non-null int64 \n 2 Application_Type 400 non-null float64 \n 3 Signal_Strength 400 non-null int64 \n 4 Latency 400 non-null int64 \n 5 Required_Bandwidth 400 non-null float64 \n 6 Allocated_Bandwidth 400 non-null float64 \n 7 Resource_Allocation 400 non-null int64 \ndtypes: datetime64[ns](1), float64(3), int64(4)\nmemory usage: 25.1 KB\n","output_type":"stream"}]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.480278Z","iopub.execute_input":"2023-09-04T15:17:56.480996Z","iopub.status.idle":"2023-09-04T15:17:56.497454Z","shell.execute_reply.started":"2023-09-04T15:17:56.480958Z","shell.execute_reply":"2023-09-04T15:17:56.496385Z"},"trusted":true},"execution_count":207,"outputs":[{"execution_count":207,"output_type":"execute_result","data":{"text/plain":" Timestamp User_ID Application_Type Signal_Strength Latency \\\n0 2023-09-03 10:00:00 1 4.0 -75 30 \n1 2023-09-03 10:00:00 2 3.0 -80 20 \n2 2023-09-03 10:00:00 3 7.0 -85 40 \n3 2023-09-03 10:00:00 4 10.0 -70 10 \n4 2023-09-03 10:00:00 5 9.0 -78 25 \n\n Required_Bandwidth Allocated_Bandwidth Resource_Allocation \n0 10000.0 15000.0 70 \n1 100.0 120.0 80 \n2 5000.0 6000.0 75 \n3 1000.0 1500.0 90 \n4 2000.0 3000.0 85 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampUser_IDApplication_TypeSignal_StrengthLatencyRequired_BandwidthAllocated_BandwidthResource_Allocation
02023-09-03 10:00:0014.0-753010000.015000.070
12023-09-03 10:00:0023.0-8020100.0120.080
22023-09-03 10:00:0037.0-85405000.06000.075
32023-09-03 10:00:00410.0-70101000.01500.090
42023-09-03 10:00:0059.0-78252000.03000.085
\n
"},"metadata":{}}]},{"cell_type":"code","source":"df.tail()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.501492Z","iopub.execute_input":"2023-09-04T15:17:56.501869Z","iopub.status.idle":"2023-09-04T15:17:56.516946Z","shell.execute_reply.started":"2023-09-04T15:17:56.501837Z","shell.execute_reply":"2023-09-04T15:17:56.515626Z"},"trusted":true},"execution_count":208,"outputs":[{"execution_count":208,"output_type":"execute_result","data":{"text/plain":" Timestamp User_ID Application_Type Signal_Strength Latency \\\n395 2023-09-03 10:06:00 396 7.0 -110 61 \n396 2023-09-03 10:06:00 397 4.0 -40 53 \n397 2023-09-03 10:06:00 398 8.0 -113 58 \n398 2023-09-03 10:06:00 399 10.0 -40 5 \n399 2023-09-03 10:06:00 400 1.0 -113 0 \n\n Required_Bandwidth Allocated_Bandwidth Resource_Allocation \n395 1300.0 1800.0 85 \n396 14500.0 15800.0 75 \n397 1000.0 1400.0 70 \n398 400.0 400.0 70 \n399 100.0 100.0 70 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampUser_IDApplication_TypeSignal_StrengthLatencyRequired_BandwidthAllocated_BandwidthResource_Allocation
3952023-09-03 10:06:003967.0-110611300.01800.085
3962023-09-03 10:06:003974.0-405314500.015800.075
3972023-09-03 10:06:003988.0-113581000.01400.070
3982023-09-03 10:06:0039910.0-405400.0400.070
3992023-09-03 10:06:004001.0-1130100.0100.070
\n
"},"metadata":{}}]},{"cell_type":"code","source":"df.describe()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.565907Z","iopub.execute_input":"2023-09-04T15:17:56.566287Z","iopub.status.idle":"2023-09-04T15:17:56.604778Z","shell.execute_reply.started":"2023-09-04T15:17:56.566257Z","shell.execute_reply":"2023-09-04T15:17:56.603775Z"},"trusted":true},"execution_count":209,"outputs":[{"execution_count":209,"output_type":"execute_result","data":{"text/plain":" Timestamp User_ID Application_Type Signal_Strength \\\ncount 400 400.000000 400.000000 400.000000 \nmean 2023-09-03 10:03:00 200.500000 5.605000 -80.495000 \nmin 2023-09-03 10:00:00 1.000000 0.000000 -123.000000 \n25% 2023-09-03 10:01:00 100.750000 2.000000 -98.000000 \n50% 2023-09-03 10:03:00 200.500000 6.000000 -83.000000 \n75% 2023-09-03 10:05:00 300.250000 8.000000 -64.000000 \nmax 2023-09-03 10:06:00 400.000000 10.000000 -40.000000 \nstd NaN 115.614301 3.156562 20.701119 \n\n Latency Required_Bandwidth Allocated_Bandwidth \\\ncount 400.000000 400.000000 400.00000 \nmean 33.825000 3135.512500 3502.38000 \nmin 0.000000 0.000000 0.00000 \n25% 21.750000 417.500000 417.50000 \n50% 31.000000 1200.000000 1350.00000 \n75% 45.000000 4100.000000 4425.00000 \nmax 110.000000 14500.000000 15800.00000 \nstd 21.122139 3984.096715 4460.80117 \n\n Resource_Allocation \ncount 400.000000 \nmean 74.712500 \nmin 50.000000 \n25% 70.000000 \n50% 70.000000 \n75% 80.000000 \nmax 90.000000 \nstd 8.982291 ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampUser_IDApplication_TypeSignal_StrengthLatencyRequired_BandwidthAllocated_BandwidthResource_Allocation
count400400.000000400.000000400.000000400.000000400.000000400.00000400.000000
mean2023-09-03 10:03:00200.5000005.605000-80.49500033.8250003135.5125003502.3800074.712500
min2023-09-03 10:00:001.0000000.000000-123.0000000.0000000.0000000.0000050.000000
25%2023-09-03 10:01:00100.7500002.000000-98.00000021.750000417.500000417.5000070.000000
50%2023-09-03 10:03:00200.5000006.000000-83.00000031.0000001200.0000001350.0000070.000000
75%2023-09-03 10:05:00300.2500008.000000-64.00000045.0000004100.0000004425.0000080.000000
max2023-09-03 10:06:00400.00000010.000000-40.000000110.00000014500.00000015800.0000090.000000
stdNaN115.6143013.15656220.70111921.1221393984.0967154460.801178.982291
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"},"metadata":{}}]},{"cell_type":"code","source":"# 'User_ID' having very less effect on result, so remove it\ndf.drop('User_ID', axis=1, inplace=True)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.640447Z","iopub.execute_input":"2023-09-04T15:17:56.640869Z","iopub.status.idle":"2023-09-04T15:17:56.647973Z","shell.execute_reply.started":"2023-09-04T15:17:56.640834Z","shell.execute_reply":"2023-09-04T15:17:56.646629Z"},"trusted":true},"execution_count":210,"outputs":[]},{"cell_type":"code","source":"df","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.659955Z","iopub.execute_input":"2023-09-04T15:17:56.660309Z","iopub.status.idle":"2023-09-04T15:17:56.681737Z","shell.execute_reply.started":"2023-09-04T15:17:56.660279Z","shell.execute_reply":"2023-09-04T15:17:56.680489Z"},"trusted":true},"execution_count":211,"outputs":[{"execution_count":211,"output_type":"execute_result","data":{"text/plain":" Timestamp Application_Type Signal_Strength Latency \\\n0 2023-09-03 10:00:00 4.0 -75 30 \n1 2023-09-03 10:00:00 3.0 -80 20 \n2 2023-09-03 10:00:00 7.0 -85 40 \n3 2023-09-03 10:00:00 10.0 -70 10 \n4 2023-09-03 10:00:00 9.0 -78 25 \n.. ... ... ... ... \n395 2023-09-03 10:06:00 7.0 -110 61 \n396 2023-09-03 10:06:00 4.0 -40 53 \n397 2023-09-03 10:06:00 8.0 -113 58 \n398 2023-09-03 10:06:00 10.0 -40 5 \n399 2023-09-03 10:06:00 1.0 -113 0 \n\n Required_Bandwidth Allocated_Bandwidth Resource_Allocation \n0 10000.0 15000.0 70 \n1 100.0 120.0 80 \n2 5000.0 6000.0 75 \n3 1000.0 1500.0 90 \n4 2000.0 3000.0 85 \n.. ... ... ... \n395 1300.0 1800.0 85 \n396 14500.0 15800.0 75 \n397 1000.0 1400.0 70 \n398 400.0 400.0 70 \n399 100.0 100.0 70 \n\n[400 rows x 7 columns]","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
TimestampApplication_TypeSignal_StrengthLatencyRequired_BandwidthAllocated_BandwidthResource_Allocation
02023-09-03 10:00:004.0-753010000.015000.070
12023-09-03 10:00:003.0-8020100.0120.080
22023-09-03 10:00:007.0-85405000.06000.075
32023-09-03 10:00:0010.0-70101000.01500.090
42023-09-03 10:00:009.0-78252000.03000.085
........................
3952023-09-03 10:06:007.0-110611300.01800.085
3962023-09-03 10:06:004.0-405314500.015800.075
3972023-09-03 10:06:008.0-113581000.01400.070
3982023-09-03 10:06:0010.0-405400.0400.070
3992023-09-03 10:06:001.0-1130100.0100.070
\n

400 rows × 7 columns

\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Data Visualization :**","metadata":{}},{"cell_type":"code","source":"# Find count of values in target variable\nsns.countplot(x=df['Resource_Allocation'])","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:56.720520Z","iopub.execute_input":"2023-09-04T15:17:56.720915Z","iopub.status.idle":"2023-09-04T15:17:57.029416Z","shell.execute_reply.started":"2023-09-04T15:17:56.720885Z","shell.execute_reply":"2023-09-04T15:17:57.028618Z"},"trusted":true},"execution_count":212,"outputs":[{"execution_count":212,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"# Finding Outliers\n\nsns.boxplot(data=df, orient=\"h\", palette=\"Set2\") # Use sns.violinplot() for a violin plot\n","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:57.031091Z","iopub.execute_input":"2023-09-04T15:17:57.031845Z","iopub.status.idle":"2023-09-04T15:17:57.379692Z","shell.execute_reply.started":"2023-09-04T15:17:57.031811Z","shell.execute_reply":"2023-09-04T15:17:57.378585Z"},"trusted":true},"execution_count":213,"outputs":[{"execution_count":213,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"sns.boxplot(data=df['Signal_Strength'])\n# No outtliers present","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:57.381319Z","iopub.execute_input":"2023-09-04T15:17:57.381788Z","iopub.status.idle":"2023-09-04T15:17:57.599781Z","shell.execute_reply.started":"2023-09-04T15:17:57.381746Z","shell.execute_reply":"2023-09-04T15:17:57.598765Z"},"trusted":true},"execution_count":214,"outputs":[{"execution_count":214,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"sns.boxplot(data=df['Latency']) \n# Outliers present on positive side","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:57.603641Z","iopub.execute_input":"2023-09-04T15:17:57.604064Z","iopub.status.idle":"2023-09-04T15:17:57.801568Z","shell.execute_reply.started":"2023-09-04T15:17:57.604031Z","shell.execute_reply":"2023-09-04T15:17:57.800751Z"},"trusted":true},"execution_count":215,"outputs":[{"execution_count":215,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"# Cannot transform latency data to handle outliers=> Leads to greater number of outliers\n# So, Removing outliers from 'Latency'\n\nQ1 = np.percentile(df['Latency'], 25, method='midpoint')\nQ3 = np.percentile(df['Latency'], 75, method='midpoint')\n\nIQR = Q3-Q1\n\nupper = Q3 + 1.5*IQR\nlower = Q1 - 1.5*IQR\n\nupper_val = np.where(df['Latency'] >= upper)\nlower_val = np.where(df['Latency'] <= lower)\n\n# Removing the outliers\ndf.drop(upper_val[0], inplace=True)\ndf.drop(lower_val[0], inplace=True)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:57.803243Z","iopub.execute_input":"2023-09-04T15:17:57.803974Z","iopub.status.idle":"2023-09-04T15:17:57.816805Z","shell.execute_reply.started":"2023-09-04T15:17:57.803922Z","shell.execute_reply":"2023-09-04T15:17:57.815931Z"},"trusted":true},"execution_count":216,"outputs":[]},{"cell_type":"code","source":"sns.boxplot(data=df['Latency']) ","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:57.818394Z","iopub.execute_input":"2023-09-04T15:17:57.819119Z","iopub.status.idle":"2023-09-04T15:17:58.009075Z","shell.execute_reply.started":"2023-09-04T15:17:57.819078Z","shell.execute_reply":"2023-09-04T15:17:58.007674Z"},"trusted":true},"execution_count":217,"outputs":[{"execution_count":217,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"iVBORw0KGgoAAAANSUhEUgAAAh8AAAGdCAYAAACyzRGfAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAd+UlEQVR4nO3df2xV9f3H8dctbe+9Uu7BVrmXhlvtHFvxB6AVy1X2i92laxwRaJwYlqES2Vxhg845ugjMTS2STRhaYJquYLRflGSwOdOa2UWMrq1YdNG4VNyI7VbvRZf1Xui4t0jP9w/jHVfQcdvbz+0tz0dykt5zzj33XRpynzn33Hsdtm3bAgAAMCQn0wMAAIBzC/EBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo3IzPcDHDQ0Nqa+vT5MmTZLD4cj0OAAA4CzYtq2jR4+quLhYOTmffm5jzMVHX1+f/H5/pscAAADD0Nvbq2nTpn3qPmMuPiZNmiTpw+E9Hk+GpwEAAGcjGo3K7/cnnsc/zZiLj49eavF4PMQHAABZ5mwumeCCUwAAYFRK8XHy5EmtW7dOpaWlcrvduuSSS/Tzn/9cp34xrm3bWr9+vaZOnSq3261gMKhDhw6lfXAAAJCdUoqPBx54QNu3b9fDDz+sv/71r3rggQe0adMmPfTQQ4l9Nm3apK1bt2rHjh3q7OzUxIkTVVlZqVgslvbhAQBA9nHYp562+B++8Y1vyOv1qrGxMbGuurpabrdbjz/+uGzbVnFxsX74wx/qzjvvlCRFIhF5vV7t3LlTS5Ys+Z+PEY1GZVmWIpEI13wAAJAlUnn+TunMx7XXXqu2tja99dZbkqS//OUvevHFF1VVVSVJOnz4sEKhkILBYOI+lmWpoqJC7e3tZzxmPB5XNBpNWgAAwPiV0rtd1q5dq2g0qrKyMk2YMEEnT57Ufffdp6VLl0qSQqGQJMnr9Sbdz+v1JrZ9XH19ve65557hzA4AALJQSmc+nnrqKT3xxBNqbm7WwYMHtWvXLv3iF7/Qrl27hj1AXV2dIpFIYunt7R32sQAAwNiX0pmPH/3oR1q7dm3i2o0rrrhC77zzjurr67Vs2TL5fD5JUjgc1tSpUxP3C4fDmj179hmP6XQ65XQ6hzk+AADINimd+fjPf/5z2ue1T5gwQUNDQ5Kk0tJS+Xw+tbW1JbZHo1F1dnYqEAikYVwAAJDtUjrzsWDBAt13330qKSnRZZddpldffVUPPvigbrvtNkkffqrZ6tWrde+992r69OkqLS3VunXrVFxcrIULF47G/AAAIMukFB8PPfSQ1q1bp+9973s6cuSIiouL9Z3vfEfr169P7HPXXXdpYGBAK1asUH9/v+bNm6fW1la5XK60Dw8AALJPSp/zYQKf84F0sm2bD7gbI2zbVjwel/ThtV5n8/0PMMPlcvH3wIil8vw95r5YDkinWCyW+BwaAGfW0tIit9ud6TFwDuGL5QAAgFGc+cC45nK51NLSkukxoA/PQi1atEiStHfvXq4DG0P4W8A04gPjmsPh4HTyGORyufi7AOcwXnYBAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKNSio+LL75YDofjtKWmpkaSFIvFVFNTo6KiIhUUFKi6ulrhcHhUBgcAANkppfg4cOCA3n333cTyxz/+UZJ04403SpLWrFmjp59+Wnv27NH+/fvV19enxYsXp39qAACQtXJT2fnCCy9Mur1x40Zdcskl+tKXvqRIJKLGxkY1Nzdr/vz5kqSmpibNmDFDHR0dmjt3bvqmBgAAWWvY13wMDg7q8ccf12233SaHw6Guri6dOHFCwWAwsU9ZWZlKSkrU3t7+iceJx+OKRqNJCwAAGL+GHR/79u1Tf3+/brnlFklSKBRSfn6+Jk+enLSf1+tVKBT6xOPU19fLsqzE4vf7hzsSAADIAsOOj8bGRlVVVam4uHhEA9TV1SkSiSSW3t7eER0PAACMbSld8/GRd955R88995x++9vfJtb5fD4NDg6qv78/6exHOByWz+f7xGM5nU45nc7hjAEAALLQsM58NDU1acqUKbr++usT68rLy5WXl6e2trbEuu7ubvX09CgQCIx8UgAAMC6kfOZjaGhITU1NWrZsmXJz/3t3y7K0fPly1dbWqrCwUB6PR6tWrVIgEOCdLgAAICHl+HjuuefU09Oj22677bRtmzdvVk5OjqqrqxWPx1VZWalt27alZVAAADA+OGzbtjM9xKmi0agsy1IkEpHH48n0OADS5Pjx46qqqpIktbS0yO12Z3giAOmUyvM33+0CAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgVMrx8c9//lPf+ta3VFRUJLfbrSuuuEKvvPJKYrtt21q/fr2mTp0qt9utYDCoQ4cOpXVoAACQvVKKj3//+9+67rrrlJeXp5aWFr355pv65S9/qfPPPz+xz6ZNm7R161bt2LFDnZ2dmjhxoiorKxWLxdI+PAAAyD65qez8wAMPyO/3q6mpKbGutLQ08bNt29qyZYvuvvtu3XDDDZKkxx57TF6vV/v27dOSJUvSNDYAAMhWKZ35+P3vf6+rr75aN954o6ZMmaIrr7xSjz76aGL74cOHFQqFFAwGE+ssy1JFRYXa29vPeMx4PK5oNJq0AACA8Sul+Pj73/+u7du3a/r06Xr22Wd1xx136Pvf/7527dolSQqFQpIkr9ebdD+v15vY9nH19fWyLCux+P3+4fweAAAgS6QUH0NDQ7rqqqt0//3368orr9SKFSt0++23a8eOHcMeoK6uTpFIJLH09vYO+1gAAGDsSyk+pk6dqksvvTRp3YwZM9TT0yNJ8vl8kqRwOJy0TzgcTmz7OKfTKY/Hk7QAAIDxK6X4uO6669Td3Z207q233tJFF10k6cOLT30+n9ra2hLbo9GoOjs7FQgE0jAuAADIdim922XNmjW69tprdf/99+ub3/ymXn75ZT3yyCN65JFHJEkOh0OrV6/Wvffeq+nTp6u0tFTr1q1TcXGxFi5cOBrzAwCALJNSfMyZM0d79+5VXV2dfvazn6m0tFRbtmzR0qVLE/vcddddGhgY0IoVK9Tf36958+aptbVVLpcr7cMDAIDs47Bt2870EKeKRqOyLEuRSITrP4Bx5Pjx46qqqpIktbS0yO12Z3giAOmUyvM33+0CAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgVErx8dOf/lQOhyNpKSsrS2yPxWKqqalRUVGRCgoKVF1drXA4nPahAQBA9kr5zMdll12md999N7G8+OKLiW1r1qzR008/rT179mj//v3q6+vT4sWL0zowAADIbrkp3yE3Vz6f77T1kUhEjY2Nam5u1vz58yVJTU1NmjFjhjo6OjR37tyRTwsAALJeymc+Dh06pOLiYn3mM5/R0qVL1dPTI0nq6urSiRMnFAwGE/uWlZWppKRE7e3tn3i8eDyuaDSatAAAgPErpfioqKjQzp071draqu3bt+vw4cP6whe+oKNHjyoUCik/P1+TJ09Ouo/X61UoFPrEY9bX18uyrMTi9/uH9YsAAIDskNLLLlVVVYmfZ86cqYqKCl100UV66qmn5Ha7hzVAXV2damtrE7ej0SgBAgDAODait9pOnjxZn/vc5/T222/L5/NpcHBQ/f39SfuEw+EzXiPyEafTKY/Hk7QAAIDxa0TxcezYMf3tb3/T1KlTVV5erry8PLW1tSW2d3d3q6enR4FAYMSDAgCA8SGll13uvPNOLViwQBdddJH6+vq0YcMGTZgwQTfffLMsy9Ly5ctVW1urwsJCeTwerVq1SoFAgHe6AACAhJTi4x//+Iduvvlm/etf/9KFF16oefPmqaOjQxdeeKEkafPmzcrJyVF1dbXi8bgqKyu1bdu2URkcAABkJ4dt23amhzhVNBqVZVmKRCJc/wGMI8ePH09ctN7S0jLsi9QBjE2pPH/z3S4AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMCo3EwPMB7Ztq1YLJbpMYAx5dT/E/z/AM7M5XLJ4XBkeoxRR3yMglgspqqqqkyPAYxZixYtyvQIwJjU0tIit9ud6TFGHS+7AAAAozjzMcqOzb5Zdg7/zIBsWxr64MOfc3Klc+DUMnA2HEMfqOC1/8v0GEbxrDjK7JxcaUJepscAxoj8TA8AjDl2pgfIAF52AQAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAqBHFx8aNG+VwOLR69erEulgsppqaGhUVFamgoEDV1dUKh8MjnRMAAIwTw46PAwcO6Ne//rVmzpyZtH7NmjV6+umntWfPHu3fv199fX1avHjxiAcFAADjw7Di49ixY1q6dKkeffRRnX/++Yn1kUhEjY2NevDBBzV//nyVl5erqalJf/7zn9XR0ZG2oQEAQPYaVnzU1NTo+uuvVzAYTFrf1dWlEydOJK0vKytTSUmJ2tvbz3iseDyuaDSatAAAgPErN9U77N69WwcPHtSBAwdO2xYKhZSfn6/Jkycnrfd6vQqFQmc8Xn19ve65555UxwAAAFkqpTMfvb29+sEPfqAnnnhCLpcrLQPU1dUpEokklt7e3rQcFwAAjE0pxUdXV5eOHDmiq666Srm5ucrNzdX+/fu1detW5ebmyuv1anBwUP39/Un3C4fD8vl8Zzym0+mUx+NJWgAAwPiV0ssuX/3qV/X6668nrbv11ltVVlamH//4x/L7/crLy1NbW5uqq6slSd3d3erp6VEgEEjf1AAAIGulFB+TJk3S5ZdfnrRu4sSJKioqSqxfvny5amtrVVhYKI/Ho1WrVikQCGju3LnpmxoAAGStlC84/V82b96snJwcVVdXKx6Pq7KyUtu2bUv3wwAAgCw14vh4/vnnk267XC41NDSooaFhpIcGAADjEN/tAgAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABiVm+kBxiPbtv974+SJzA0CABj7TnmeSHr+GMeIj1EQj8cTP0/6y+4MTgIAyCbxeFznnXdepscYdSm97LJ9+3bNnDlTHo9HHo9HgUBALS0tie2xWEw1NTUqKipSQUGBqqurFQ6H0z40AADIXimd+Zg2bZo2btyo6dOny7Zt7dq1SzfccINeffVVXXbZZVqzZo2eeeYZ7dmzR5ZlaeXKlVq8eLFeeuml0Zp/THI6nYmfj85aIk3Iy+A0AIAx7eSJxFnyU58/xrOU4mPBggVJt++77z5t375dHR0dmjZtmhobG9Xc3Kz58+dLkpqamjRjxgx1dHRo7ty56Zt6jHM4HP+9MSGP+AAAnJWk549xbNjvdjl58qR2796tgYEBBQIBdXV16cSJEwoGg4l9ysrKVFJSovb29k88TjweVzQaTVoAAMD4lXJ8vP766yooKJDT6dR3v/td7d27V5deeqlCoZDy8/M1efLkpP29Xq9CodAnHq++vl6WZSUWv9+f8i8BAACyR8rx8fnPf16vvfaaOjs7dccdd2jZsmV68803hz1AXV2dIpFIYunt7R32sQAAwNiX8ltt8/Pz9dnPflaSVF5ergMHDuhXv/qVbrrpJg0ODqq/vz/p7Ec4HJbP5/vE4zmdznPmAhsAAJCGTzgdGhpSPB5XeXm58vLy1NbWltjW3d2tnp4eBQKBkT4MAAAYJ1I681FXV6eqqiqVlJTo6NGjam5u1vPPP69nn31WlmVp+fLlqq2tVWFhoTwej1atWqVAIHBOvdMFAAB8upTi48iRI/r2t7+td999V5ZlaebMmXr22Wf1ta99TZK0efNm5eTkqLq6WvF4XJWVldq2bduoDA4AALJTSvHR2Nj4qdtdLpcaGhrU0NAwoqEAAMD4xbfaAgAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEblZnqA8c4x9IHsTA8BjAW2LQ198OHPObmSw5HZeYAxwvHR/4tzCPExygpe+79MjwAAwJiS0ssu9fX1mjNnjiZNmqQpU6Zo4cKF6u7uTtonFouppqZGRUVFKigoUHV1tcLhcFqHBgAA2cth2/ZZvyrw9a9/XUuWLNGcOXP0wQcf6Cc/+YneeOMNvfnmm5o4caIk6Y477tAzzzyjnTt3yrIsrVy5Ujk5OXrppZfO6jGi0agsy1IkEpHH4xneb5Vhtm0rFotlegxgTInFYlq0aJEkae/evXK5XBmeCBh7XC6XHFn6kmQqz98pvezS2tqadHvnzp2aMmWKurq69MUvflGRSESNjY1qbm7W/PnzJUlNTU2aMWOGOjo6NHfu3BR/lezkcDjkdrszPQYwZrlcLv6PAOewEb3bJRKJSJIKCwslSV1dXTpx4oSCwWBin7KyMpWUlKi9vf2Mx4jH44pGo0kLAAAYv4YdH0NDQ1q9erWuu+46XX755ZKkUCik/Px8TZ48OWlfr9erUCh0xuPU19fLsqzE4vf7hzsSAADIAsOOj5qaGr3xxhvavXv3iAaoq6tTJBJJLL29vSM6HgAAGNuG9VbblStX6g9/+INeeOEFTZs2LbHe5/NpcHBQ/f39SWc/wuGwfD7fGY/ldDrldDqHMwYAAMhCKZ35sG1bK1eu1N69e/WnP/1JpaWlSdvLy8uVl5entra2xLru7m719PQoEAikZ2IAAJDVUjrzUVNTo+bmZv3ud7/TpEmTEtdxWJYlt9sty7K0fPly1dbWqrCwUB6PR6tWrVIgEDhn3ukCAAA+XUrxsX37dknSl7/85aT1TU1NuuWWWyRJmzdvVk5OjqqrqxWPx1VZWalt27alZVgAAJD9UoqPs/k8MpfLpYaGBjU0NAx7KAAAMH7xrbYAAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGpRwfL7zwghYsWKDi4mI5HA7t27cvabtt21q/fr2mTp0qt9utYDCoQ4cOpWteAACQ5VKOj4GBAc2aNUsNDQ1n3L5p0yZt3bpVO3bsUGdnpyZOnKjKykrFYrERDwsAALJfbqp3qKqqUlVV1Rm32batLVu26O6779YNN9wgSXrsscfk9Xq1b98+LVmyZGTTAgCArJfWaz4OHz6sUCikYDCYWGdZlioqKtTe3n7G+8TjcUWj0aQFAACMX2mNj1AoJEnyer1J671eb2Lbx9XX18uyrMTi9/vTORIAABhjMv5ul7q6OkUikcTS29ub6ZEAAMAoSmt8+Hw+SVI4HE5aHw6HE9s+zul0yuPxJC0AAGD8Smt8lJaWyufzqa2tLbEuGo2qs7NTgUAgnQ8FAACyVMrvdjl27JjefvvtxO3Dhw/rtddeU2FhoUpKSrR69Wrde++9mj59ukpLS7Vu3ToVFxdr4cKF6ZwbAABkqZTj45VXXtFXvvKVxO3a2lpJ0rJly7Rz507dddddGhgY0IoVK9Tf36958+aptbVVLpcrfVMDAICs5bBt2870EKeKRqOyLEuRSITrP4Bx5Pjx44nPCGppaZHb7c7wRADSKZXn74y/2wUAAJxbiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYNWrx0dDQoIsvvlgul0sVFRV6+eWXR+uhAABAFhmV+HjyySdVW1urDRs26ODBg5o1a5YqKyt15MiR0Xg4AACQRXJH46APPvigbr/9dt16662SpB07duiZZ57Rb37zG61du3Y0HhI4I9u2FYvFMj0GpKS/A3+TscXlcsnhcGR6DJxD0h4fg4OD6urqUl1dXWJdTk6OgsGg2tvbT9s/Ho8rHo8nbkej0XSPhHNYLBZTVVVVpsfAxyxatCjTI+AULS0tcrvdmR4D55C0v+zy/vvv6+TJk/J6vUnrvV6vQqHQafvX19fLsqzE4vf70z0SAAAYQ0blZZdU1NXVqba2NnE7Go0SIEgbl8ullpaWTI8BffgS2EdnOZ1OJ6f5xxCXy5XpEXCOSXt8XHDBBZowYYLC4XDS+nA4LJ/Pd9r+TqdTTqcz3WMAkiSHw8Hp5DHkvPPOy/QIAMaAtL/skp+fr/LycrW1tSXWDQ0Nqa2tTYFAIN0PBwAAssyovOxSW1urZcuW6eqrr9Y111yjLVu2aGBgIPHuFwAAcO4alfi46aab9N5772n9+vUKhUKaPXu2WltbT7sIFQAAnHsctm3bmR7iVNFoVJZlKRKJyOPxZHocAABwFlJ5/ua7XQAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFGj8vHqI/HRB65Go9EMTwIAAM7WR8/bZ/PB6WMuPo4ePSpJ8vv9GZ4EAACk6ujRo7Is61P3GXPf7TI0NKS+vj5NmjRJDocj0+MASKNoNCq/36/e3l6+uwkYZ2zb1tGjR1VcXKycnE+/qmPMxQeA8YsvjgQgccEpAAAwjPgAAABGER8AjHE6ndqwYYOcTmemRwGQQVzzAQAAjOLMBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAMKahoUEXX3yxXC6XKioq9PLLL2d6JAAZQHwAMOLJJ59UbW2tNmzYoIMHD2rWrFmqrKzUkSNHMj0aAMN4qy0AIyoqKjRnzhw9/PDDkj78Hie/369Vq1Zp7dq1GZ4OgEmc+QAw6gYHB9XV1aVgMJhYl5OTo2AwqPb29gxOBiATiA8Ao+7999/XyZMn5fV6k9Z7vV6FQqEMTQUgU4gPAABgFPEBYNRdcMEFmjBhgsLhcNL6cDgsn8+XoakAZArxAWDU5efnq7y8XG1tbYl1Q0NDamtrUyAQyOBkADIhN9MDADg31NbWatmyZbr66qt1zTXXaMuWLRoYGNCtt96a6dEAGEZ8ADDipptu0nvvvaf169crFApp9uzZam1tPe0iVADjH5/zAQAAjOKaDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAw6v8BVl+pbMqibBIAAAAASUVORK5CYII="},"metadata":{}}]},{"cell_type":"code","source":"df.shape","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:58.011440Z","iopub.execute_input":"2023-09-04T15:17:58.012364Z","iopub.status.idle":"2023-09-04T15:17:58.020984Z","shell.execute_reply.started":"2023-09-04T15:17:58.012312Z","shell.execute_reply":"2023-09-04T15:17:58.019610Z"},"trusted":true},"execution_count":218,"outputs":[{"execution_count":218,"output_type":"execute_result","data":{"text/plain":"(387, 7)"},"metadata":{}}]},{"cell_type":"code","source":"sns.boxplot(data=df['Required_Bandwidth']) \n# Outliers present on positive side","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:58.022606Z","iopub.execute_input":"2023-09-04T15:17:58.023005Z","iopub.status.idle":"2023-09-04T15:17:58.208004Z","shell.execute_reply.started":"2023-09-04T15:17:58.022974Z","shell.execute_reply":"2023-09-04T15:17:58.206889Z"},"trusted":true},"execution_count":219,"outputs":[{"execution_count":219,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"# Can handle outliers in 'Required_Bandwidth', using Transformation\n# So, use \"Square Root Transformation (np.sqrt())\"\"\n\ndf['Required_Bandwidth'] = np.sqrt(df['Required_Bandwidth'])\n\nsns.boxplot(data=df['Required_Bandwidth']) ","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:58.209524Z","iopub.execute_input":"2023-09-04T15:17:58.209924Z","iopub.status.idle":"2023-09-04T15:17:58.380354Z","shell.execute_reply.started":"2023-09-04T15:17:58.209894Z","shell.execute_reply":"2023-09-04T15:17:58.379165Z"},"trusted":true},"execution_count":220,"outputs":[{"execution_count":220,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
","image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":"df['Allocated_Bandwidth'] = np.sqrt(df['Allocated_Bandwidth'])\n\nsns.boxplot(data=df['Allocated_Bandwidth']) ","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:58.384649Z","iopub.execute_input":"2023-09-04T15:17:58.385023Z","iopub.status.idle":"2023-09-04T15:17:58.555649Z","shell.execute_reply.started":"2023-09-04T15:17:58.384993Z","shell.execute_reply":"2023-09-04T15:17:58.554548Z"},"trusted":true},"execution_count":221,"outputs":[{"execution_count":221,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"sns.boxplot(data=df) \n# Outliers removed from all the columns\n# But data is present over very wide ranges\n# So, have to normalize data to one range","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:58.557355Z","iopub.execute_input":"2023-09-04T15:17:58.557990Z","iopub.status.idle":"2023-09-04T15:17:58.815698Z","shell.execute_reply.started":"2023-09-04T15:17:58.557956Z","shell.execute_reply":"2023-09-04T15:17:58.814553Z"},"trusted":true},"execution_count":222,"outputs":[{"execution_count":222,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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dnfZVhSU1P5LTIAACpIjQ9P5e01klTu6X2tvPXQcwUAwMnV+PBU1XqNfCElJaVc09NzBQDAyXHAOAAAgA01vufJGGPd/719X8kZ4I8ipKLCY/edAZI/dpkVFSos4+3/lmNOMzIAADVXjQ9PxWe5SbLCQ02Xn5+v0NBQf5cBAECVxG47AAAAG2p8z5PL5bLus9vuWM9byTYBAADeanx4KnlKPrvtjuEyBQAAnBy77QAAAGyoNj1P06ZN0/PPP6+srCy1b99eU6dO1UUXXVTu+brdbqWmpvqgwjPn8XisazMtWrRIbrfbr/X4e/kAAFRl1SI8vf322xo5cqSmT5+uzp07a8qUKUpOTtbmzZtVv379cs3b4XCU+4KQvrhKuS9xhXAAACpOtQhPL774ooYOHapbb71VkjR9+nQtXbpUM2fO1EMPPeTn6nx7lfLyXh1c4grhKH+gLzmtL74YVOdAT1v6hq9/CoufoYI/VfnwdOTIEa1fv15jx461nnM6nerevbvS0tJOOE1+fr7X9ZtycnIqvE6gKiHQ+w5t6Ru+/iksfoYK/lTlw9O+fftUWFiomJgYr+djYmL0448/nnCaCRMm6K9//WtllCep/MdNGWOssOdyucr9bYhjlgAAqDhVPjydibFjx2rkyJHW45ycHMXFxVXY8nxx3BRX9IYvEeh9h7b0DV+cnOPLtqyu7YiqocqHp7p16yogIEDZ2dlez2dnZys2NvaE07hcLi70iBqNQO87tKVv+KIdJdoSVUOVv85TcHCwOnbsqBUrVljPFRUVacWKFUpMTPRjZQAAoCaq8j1PkjRy5EgNGjRInTp10kUXXaQpU6bo999/t86+AwAAqCzVIjz17dtXe/fu1bhx45SVlaU//elPWrZsWamDyAEAACqawxhj/F1ERcvJyVFkZKQOHTqkiIgIf5cDAADKoKp+flf5Y54AAACqEsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsCPR3AUAxY4w8Hk+555Gfny9JcrlccjgcZzwvt9tdrukBAGcnwhOqDI/Ho+TkZH+XYUlNTVVISIi/ywAAVDHstgMAALCBnidUGW63W6mpqeWah8fjUUpKiiRp0aJFcrvd5aoHAIDjEZ5QZTgcDp/uJnO73ex2AwD4HLvtAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABv8Gp6aNGkih8PhdXv22We9xtmwYYMuu+wyud1uxcXFaeLEiX6qFgAAoApcJPOJJ57Q0KFDrce1atWy7ufk5Ojqq69W9+7dNX36dG3cuFG33XaboqKidMcdd/ijXAAAUMP5PTzVqlVLsbGxJxw2b948HTlyRDNnzlRwcLDatm2r9PR0vfjii4QnAADgF34/5unZZ59VnTp1dMEFF+j5559XQUGBNSwtLU2XX365goODreeSk5O1efNmHThw4KTzzM/PV05OjtcNAADAF/za8/SXv/xFHTp0UHR0tL788kuNHTtWe/bs0YsvvihJysrKUtOmTb2miYmJsYbVrl37hPOdMGGC/vrXv1Zs8QAAoEbyec/TQw89VOog8ONvP/74oyRp5MiR6tq1q9q1a6dhw4Zp0qRJmjp1qvLz88tVw9ixY3Xo0CHrtmvXLl+8NAAAAN/3PD3wwAMaPHjwKcdp1qzZCZ/v3LmzCgoK9PPPP+vcc89VbGyssrOzvcYpfnyy46QkyeVyyeVy2SscAACgDHwenurVq6d69eqd0bTp6elyOp2qX7++JCkxMVGPPPKIjh49qqCgIEnS8uXLde655550lx0AAEBF8tsB42lpaZoyZYoyMjK0fft2zZs3TyNGjNCAAQOsYPR///d/Cg4O1pAhQ7Rp0ya9/fbbeumllzRy5Eh/lQ0AAGo4vx0w7nK59NZbb+nxxx9Xfn6+mjZtqhEjRngFo8jISH388ccaPny4OnbsqLp162rcuHFcpgAAAPiN38JThw4d9NVXX512vHbt2unzzz+vhIoAAABOz+/XeQIAAKhOCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADX67SCbOPsYYeTwev9ZQcvn+rkWS3G63HA6Hv8sAAPgQ4Qk+4/F4lJyc7O8yLCkpKf4uQampqQoJCfF3GQAAH2K3HQAAgA30PKFCTLv8oFwBptKXa4x0pOjY/WCn5I89ZvmFDg3/LKryFwwAqBSEJ1QIV4CRO8A/y/b/TrLKD40AgMrDbjsAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsITwAAADYQngAAAGwgPAEAANhAeAIAALAh0N8F4OxhjLHu5xf6sRA/K/naS7YJAODsQHiCz+Tn51v3h39W24+VVB35+fkKDQ31dxkAAB9itx0AAIAN9DzBZ1wul3V/2uUH5ArwYzF+lF/4v563km0CADg7EJ7gMw6Hw7rvCpDcNTQ8lVSyTQAAZwd22wEAANhAeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANgT6uwCcnfILHZJMpS/XGOlI0bH7wU7J4aj0Ev772gEAZyvCEyrE8M+i/F0CAAAVosJ22z399NO65JJLFBoaqqioqBOOs3PnTvXs2VOhoaGqX7++Ro8erYKCAq9xVq1apQ4dOsjlcqlFixaaPXt2RZUMAABwWhXW83TkyBH16dNHiYmJmjFjRqnhhYWF6tmzp2JjY/Xll19qz549uuWWWxQUFKRnnnlGkrRjxw717NlTw4YN07x587RixQrdfvvtatCggZKTkyuqdJwht9ut1NRUv9bg8XiUkpIiSVq0aJHcbrdf6/H38gEAvucwxlTogSmzZ8/W/fffr4MHD3o9/9FHH+m6667T7t27FRMTI0maPn26xowZo7179yo4OFhjxozR0qVL9f3331vT3XzzzTp48KCWLVtW5hpycnIUGRmpQ4cOKSIiwievC1XTH3/8YQXr1NRUhYSE+LkiAMCZqqqf33472y4tLU3nn3++FZwkKTk5WTk5Odq0aZM1Tvfu3b2mS05OVlpa2innnZ+fr5ycHK8bAACAL/gtPGVlZXkFJ0nW46ysrFOOk5OToz/++OOk854wYYIiIyOtW1xcnI+rBwAANZWt8PTQQw/J4XCc8vbjjz9WVK1lNnbsWB06dMi67dq1y98lAQCAs4StA8YfeOABDR48+JTjNGvWrEzzio2N1ddff+31XHZ2tjWs+G/xcyXHiYiIOOWxLC6XSy6Xq0x1AAAA2GErPNWrV0/16tXzyYITExP19NNP69dff1X9+vUlScuXL1dERITatGljjfOvf/3La7rly5crMTHRJzUAAADYVWHHPO3cuVPp6enauXOnCgsLlZ6ervT0dOXl5UmSrr76arVp00YDBw5URkaGUlNT9eijj2r48OFWr9GwYcO0fft2Pfjgg/rxxx/1yiuv6J133tGIESMqqmwAAIBTqrDrPI0bN05z5syxHl9wwQWSpJUrV6pr164KCAjQkiVLdNdddykxMVFhYWEaNGiQnnjiCWuapk2baunSpRoxYoReeuklNWrUSP/4xz+4xhMAAPCbCr/OU1VQVa8TAd/jOk8AcPaoqp/ffrtUAQAAQHVEeAIAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANhCeAAAAbCA8AQAA2EB4AgAAsIHwBAAAYAPhCQAAwAbCEwAAgA2EJwAAABsC/V0AUMwYI4/HU655lJy+vPNyu91yOBzlmgcA4OxDeEKV4fF4lJyc7LP5paSklGv61NRUhYSE+KgaAMDZgt12AAAANtDzhCrD7XYrNTW1XPMwxig/P1+S5HK5yrXbze12l6sWAMDZifCEKsPhcPhkN1loaKgPqgEA4MTYbQcAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADYQHgCAACwgfAEAABgA+EJAADABsITAACADYQnAAAAGwhPAAAANgT6u4DKYIyRJOXk5Pi5EgAAUFbFn9vFn+NVRY0IT7m5uZKkuLg4P1cCAADsys3NVWRkpL/LsDhMVYtzFaCoqEi7d+9WrVq15HA4/F3OCeXk5CguLk67du1SRESEv8up1mhL36AdfYe29B3a0jeqSzsaY5Sbm6uGDRvK6aw6RxrViJ4np9OpRo0a+buMMomIiKjSK3J1Qlv6Bu3oO7Sl79CWvlEd2rEq9TgVqzoxDgAAoBogPAEAANhAeKoiXC6Xxo8fL5fL5e9Sqj3a0jdoR9+hLX2HtvQN2rF8asQB4wAAAL5CzxMAAIANhCcAAAAbCE8AAAA2EJ6O8/jjj+tPf/qT9Xjw4MG6/vrrK3y5DodDH3zwQYUv50z4q7YmTZpoypQplb5cf6usde5sV5Ht2LVrV91///0VMu+yWLVqlRwOhw4ePChJmj17tqKiok44bnneR2Vpw7K0xanqK+s8qorq0J4V4fi6qsr22V/rTrULT2lpaQoICFDPnj0rZXkvvfSSZs+e7bP5HR/Oiu3Zs0fXXHONz5ZzMj///LMcDscpb5GRkUpOTtaaNWsqtbbyyMjIUO/evVW/fn253W41adJEffv21a+//iqp9IdNVVD8v0hPT7c9bXmCQUVveAcPHmytS0FBQWratKkefPBBeTyeClvmifj6vXumunbt6vX+iomJUZ8+ffTLL7+cdtrK3t4d71RteLIPrYr+UC1Pe/p73TyTdbIyQ0pycrICAgK0bt26SlmeHSfbhr///vt68sknK72eaheeZsyYoXvvvVefffaZdu/eXeHLi4yMrJSEHxsbWymnjMbFxWnPnj3W7YEHHlBoaKg6dOigd999V19//bUWL16srl27av/+/ZVa25nau3evrrzySkVHRys1NVWZmZmaNWuWGjZsqN9//93WvI4cOVJBVdYsPXr00J49e7R9+3ZNnjxZr732msaPH1+pNZzuvVuZ/+uhQ4dqz5492r17txYtWqRdu3ZpwIABp52usrd3x6us7Z9dZ9qekn/XzTNpz8o6IX7nzp368ssvdc8992jmzJmVskxfiI6OVq1atSp/waYayc3NNeHh4ebHH380ffv2NU8//bQ1bOXKlUaSWbJkiTn//PONy+UynTt3Nhs3brTGmTVrlomMjDQLFy40LVq0MC6Xy1x99dVm586d1jjjx4837du3tx4PGjTIpKSkWI8LCwvNc889Z5o3b26Cg4NNXFyceeqpp6zhDz74oGnZsqUJCQkxTZs2NY8++qg5cuSItXxJXrdZs2YZY4yRZBYuXGjNZ8OGDaZbt27G7Xab6OhoM3ToUJObm1uqrueff97Exsaa6Ohoc/fdd1vLKqsxY8YYSWbVqlVmx44dxuFwmHXr1nmNI8nUrVvXFBYWWu3ctGlT43A4jMPhMC1btjSSzHfffef1vzjvvPOscWJjY823335rzXPr1q2md+/epn79+iYsLMx06tTJLF++3Gu58fHxZvLkyad9DQsXLjSBgYHm6NGjJxy+Y8eOUu0+aNAgY4wxSUlJZvjw4ea+++4zderUMV27djXGGLNx40bTo0cPExYWZurXr28GDBhg9u7da80zKSnJ3HvvvWb06NGmdu3aJiYmxowfP95ruZmZmaZLly7G5XKZ1q1bm+XLl3v9n4+vKSkpyRhTtv/t8etlSZMmTTLnnXeeCQ0NNY0aNTJ33XWXte4U/29K3orr9ng85oEHHjANGzY0oaGh5qKLLjIrV6605lv8/lm2bJlJSEgwYWFhJjk52ezevdtr+ZdccompVauWCQ4ONrGxsWb48OHmxhtvNNHR0aZnz56msLDQPPPMM6ZJkybG7XabgIAAM2zYMK95LF261LRs2dK43W7TtWtX671z4MABY0zp96kxxkyePNnEx8eftI3O9H+dl5dnBg4caMLCwkxsbKx54YUXTFJSkrnvvvtO2P7HO9G4b7zxhgkNDbUeFxQUmNtuu81qk1atWpnnnnvOa3t3wQUXWOtF7dq1jSQzZMgQc+TIEet/k52dba677jpru1G/fn0jydSrV8/MnTvXPPDAA6Znz57GGGMOHDhgEhMTjSQTFBRk2rZtaxYvXmyaN29uJk+ebG6++WYTEhJiAgICzHnnnWfmz59vtUVgYGCp9WjHjh0mKSmp1PMDBgwwL7/8srXutGrVygQGBpqAgABTv379SmvPKVOmeK0TxffPO+88ExgYaKKjo81dd91lnnzySWu6Nm3amA4dOhi3222aNGliXnvtNRMaGmrCwsKM2+02UVFRpl27dtZyR48ebSSZ4OBga7vdtGlT8/e//90YY0xMTIxp1qyZNX5eXp5p1KiRCQwMtNYtl8tlLr74YjNw4EATEBBQqj1DQkJMaGioCQwMNAsWLDAJCQkmNDTUtGzZ0sTFxRm3223atWtnFixYUKb2LPb444+bm2++2WRmZprIyEhz+PDhU7b78dvnX375xfTu3duEhYWZWrVqmT59+pisrCyveXz44YemU6dOxuVymTp16pjrr7/eGjZ37lzTsWNHEx4ebmJiYky/fv1Mdna2Meb02/CSdf32229m4MCBJioqyoSEhJgePXqYLVu2WMPLuh07nWrV8/TOO+8oISFB5557rgYMGKCZM2eWSuWjR4/WpEmTtG7dOtWrV0+9evXS0aNHreGHDx/W008/rblz52rNmjU6ePCgbr755jLXMHbsWD377LN67LHH9MMPP2j+/PmKiYmxhteqVUuzZ8/WDz/8oJdeekl///vfNXnyZElS37599cADD6ht27ZWz0/fvn1LLeP3339XcnKyateurXXr1mnBggX65JNPdM8993iNt3LlSm3btk0rV67UnDlzNHv2bNtdwsHBwXI6nfrggw/UoEEDde/eXbNmzSo13hVXXCGn02n15Ozfv1+vv/66/va3v1nfiIvb+T//+Y+kY7+C/cYbb+iNN95Qbm6uevToYc0vLy9P1157rVasWKHvvvtOPXr0UK9evbRz505b9UvHesYKCgq0cOHCE35Li4uL03vvvSdJ2rx5s/bs2aOXXnrJGj5nzhwFBwdrzZo1mj59ug4ePKgrrrhCF1xwgb755hstW7ZM2dnZ+vOf/+w13zlz5igsLExr167VxIkT9cQTT2j58uWSpMLCQl1//fUKDQ3V2rVr9frrr+uRRx7xmv7rr7+WJH3yySfas2eP3n//fWtYef63TqdTL7/8sjZt2qQ5c+bo008/1YMPPihJuuSSSzRlyhRFRERY6+CoUaMkSffcc4/S0tL01ltvacOGDerTp4969Oihn376yZr34cOH9cILL+iNN97QZ599pp07d1rTS9Krr76qr776SvHx8dq4caM+/PBDhYWF6csvv1RsbKyWLVumhx9+WHPnztX06dP14osvKiAgQLNmzdLq1aslSbt27dKNN96oXr16KT09XbfffrseeuihMr320zmT//Xo0aO1evVqLVq0SB9//LFWrVqlb7/99oxr+O233/TOO++oc+fO1nNFRUVq1KiRFixYoB9++EHjxo3TY489pvr161vbu61bt+rTTz/Vtm3brN048+fP91ovBg8erF27dmn8+PHKyclRWFiYXC6XLrnkEt16662qXbu2vvjiCx09elTXXHONvv/+e0VEROi2227Ts88+qwMHDmjbtm3q1KmTOnbsqO7du6tbt2664447NHDgQN1yyy1avXq13n33XbVv316NGzdWWFiYbr/9dsXFxWnWrFlyOp267LLL9Nlnn+njjz9Wdna2XnnlFWvdOf/881W3bl2dc8456tSpU6W158MPP6yff/7Za9pPPvlE27dvV5s2bTRnzhz94x//0LRp0zR9+nRt2rRJAQEB+u677zRp0iS9++67Gj9+vP744w/dcccdyszM1MiRI7V161YVFhbq999/19SpUxUcHKwBAwZowYIFSk1N1Y4dO9S1a9cT1j569Gjt379fV1xxhbVuHTlyRN9++63at2+vtWvXKjY2VnfddZdcLpcGDRqktLQ0PfzwwyoqKtLUqVP1xhtvaPDgwfrll1/UvHlzbdq0SSNGjNCAAQOs99TpGGM0a9YsDRgwQAkJCWrRooXefffdMv8PioqKlJKSot9++02rV6/W8uXLtX37dq/Pt6VLl+qGG27Qtddeq++++04rVqzQRRddZA0/evSonnzySWVkZOiDDz7Qzz//rMGDB0s6/Ta8pMGDB+ubb77Rhx9+qLS0NBljdO2115bKAafajpWJrajlZ5dccomZMmWKMcaYo0ePmrp161rfjIu/Ub/11lvW+Pv37zchISHm7bffNsb8r+fnq6++ssbJzMw0kszatWuNMafuecrJyTEul8v6FlEWzz//vOnYsaP1+ETfmI3x7nl6/fXXTe3atU1eXp41fOnSpcbpdFpJftCgQSY+Pt4UFBRY4/Tp08f07du3zLUV1xMfH29q165tfUNzu91W79P69euNJPPaa68ZY4wZMWKEkWTmzp1rzWPKlClGknnuueeMMcZce+21RpL55JNPrHEmTpzo1XNwIm3btjVTp061Hpe158kYYx5++GHr22OPHj3MxIkTvb71FK8fxy8/KSnJXHDBBV7PPfnkk+bqq6/2em7Xrl1Gktm8ebM13aWXXuo1zoUXXmjGjBljjDHmo48+MoGBgWbPnj3W8ON7noq/TRX32BUry//2VD1Px1uwYIGpU6eO9bj4m1dJv/zyiwkICDD/+c9/vJ6/8sorzdixY63pJJmtW7daw6dNm2ZiYmKsxw0bNjTt2rUzAQEBJiwszLhcLiPJOJ1O8+6775qEhAQTFBRkvvzyS2OMMb169TKDBw82Q4YMMf369TPGGDN27FjTpk0brzqKe0jL2/Nk93+dm5trgoODzTvvvGMNL96u2OkpCQoKMmFhYSY0NNRIMq1atTI7duw45XSxsbFWr8bRo0eNy+UyMTExpqCgwFqfU1JSTN++fc2sWbNMrVq1jCTz9ddfm0suucQMHTrU2r5NnjzZ9OnTx1x11VXG6XSaqVOnGqfTaSIjI82ECRNM586djTHGvPnmm+acc845YRsmJycbp9NptUVSUpK58847vdriySefNG632+t9W9yekkxGRobVnsXrTmW15/Dhw018fLy1bjqdTq910+PxmICAAHPllVcaY4zZvHmzkWR69+5trZvdunWz2tOYY713TqfTrFu3zrz22mvG4XCYv/71r1Z7jho1ykiytkUle56K161OnTpZvSj79+83DofDNG/e3Ko7Pj7edOjQwXTp0sV6ruR70ePxmNDQUPPAAw94vRdLvqdO5+OPPzb16tWzeu8nT55s9YSXbPeT9Tx9/PHHJiAgwGsvzqZNm6z10RhjEhMTTf/+/ctUjzHGrFu3zkgq1Wt+om14cV1btmwxksyaNWus4fv27TMhISHWeluW7VhZVJuep82bN+vrr79Wv379JEmBgYHq27evZsyY4TVeYmKidT86OlrnnnuuMjMzrecCAwN14YUXWo8TEhIUFRXlNc7JZGZmKj8/X1deeeVJx3n77bfVpUsXxcbGKjw8XI8++qjt3pTMzEy1b99eYWFh1nNdunRRUVGRNm/ebD3Xtm1bBQQEWI8bNGhgHSBtR1RUlHbv3q0PP/xQ/fr1U0FBgTp37uzV21G/fn1Jx3oFJCkpKcmavlu3bpKk7du3S5K2bt0qSerdu7fCw8MVHh6ucePGSZLWr18v6VjP06hRo9S6dWtFRUUpPDxcmZmZZ9TzJElPP/20srKyNH36dLVt21bTp09XQkKCNm7ceNppO3bs6PU4IyNDK1eutGoPDw9XQkKCJGnbtm3WeO3atfOarmT7b968WXFxcYqNjbWGl/yWdTrl+d9+8sknuvLKK3XOOeeoVq1aGjhwoPbv36/Dhw+fdJqNGzeqsLBQrVq18nrdq1ev9nrNoaGhat68+Qnr+vXXX7V79241aNBA3bp1U3p6utauXatBgwbp1ltv1U033aTevXvr6NGjuuqqqxQWFqbFixfr7bff1ty5c63lZGZmevUiSN7v6/Kw+7/etm2bjhw54lVP8XbFjv79+ys9PV0ZGRn64osv1KJFC1199dXKzc21xpk2bZo6duyoevXqKTQ0VFlZWXI6j22iAwMD1aRJEwUEBHitF7GxsVb7FxYWKjAwUB07dlRmZqa6dOlibd+kY9uQrVu3qn379vroo48UExOjkJAQ3XHHHfruu++Ul5en1atXKykpSYWFhXryySe1aNEi/etf/1J4eLhWrFihoqIir7Zwu91ebZGRkSGPx6MxY8aUak+XyyVjjNWexetOZbRneHi4Xn/9deXl5VnrZs+ePXXOOedY62ZxD9KqVasUHh6u9u3bS5I++ugja90cPXq0JOn555/Xgw8+qB9++EHt27fXqlWr9PnnnysoKEj33HOP1Z579+6VJK/tdrHidSs6Otp6Ljo6WoGBgdb2tth//vOfUp87xe/FrVu36vDhw5o2bZqys7Otdi/5njqdmTNnqm/fvgoMDJQk9evXT2vWrCnz9JmZmYqLi1NcXJz1XJs2bbw+W9PT00/52bl+/Xr16tVLjRs3Vq1atazPGDufCZmZmQoMDPRaR+vUqVMqB5xqO1ZW1SY8zZgxQwUFBWrYsKECAwMVGBioV199Ve+9954OHTpUKTWEhISccnhaWpr69++va6+9VkuWLNF3332nRx55pMIOTA0KCvJ67HA4VFRUdEbzcrvduuqqq/T444/rL3/5ixo0aKDx48dr/vz5tuf1xx9/SJI+//xzpaenKz09XW+//bYkWW+uUaNGaeHChXrmmWes8c4///xytVWdOnXUp08fvfDCC8rMzFTDhg31wgsvnHa6kiFVOhbsincZlbz99NNPuvzyy63xfNn+xzvTef/888+67rrr1K5dO7333ntav369pk2bJunUB0jn5eUpICBA69ev93rNmZmZXt3jJ6rL/HdXacn3R1hYmFq0aKH27dtr5syZWrt2rWbMmGFtPCdOnKi//OUvio+P14YNG/TDDz/Y2k3gdDpL7aIt2S1/Mmf6vy6vyMhItWjRQi1atFCXLl00Y8YM/fTTT9b74q233tKoUaM0ZMgQffzxx+rfv7+kYx84xdu7LVu2KDs722t7dybrXNeuXfXzzz/L4/EoKSlJ0dHRat26tb744gsrPD3//PN66aWXdN5556lLly5KT08vU4DNy8tTaGioRo0a5dWezz77bKmTTkquO3bZbc/09HTdeuutKioqstbN6OhodezY0Vo38/LyJEnnnXee0tPTNXnyZAUEBOj777+31s1rrrlGERERSkpK0u7du3XllVfK6XRq1apV+ve//62oqCiv9vziiy9KvebjnWi9Pf59dvzjks8V1118WEBxm5f1PfXbb79p4cKFeuWVV6x17ZxzzlFBQYFPDxw/1edn8aEqERERmjdvntatW6eFCxdKqpgTO061HSurahGeCgoKNHfuXE2aNMnrDZmRkaGGDRvqn//8pzXuV199Zd0/cOCAtmzZotatW3vN65tvvrEeb968WQcPHvQa52RatmypkJAQrVix4oTDv/zyS8XHx+uRRx5Rp06d1LJly1KnzwYHB6uwsPCUy2ndurUyMjK8zhRbs2aNnE6n7W9oZ+L222/X7t27tX//fhUUFHgNKw4/n3/+ufXcqlWrJEnNmjWTJLVq1cp6XLyBa9y4saRjr1869noGDx6sG264Qeeff75iY2NLHY9QHsHBwWrevLnVhsXLPV3bS1KHDh20adMmNWnSxKq/+Hb8h+/JnHvuudq1a5eys7Ot544//ddOTWW1fv16FRUVadKkSbr44ovVqlWrUmdpnWgdvOCCC1RYWKhff/211Gsu2Xt2KrVq1VKTJk20Z88er+edTqcefvhhPfroo0pMTJTT6dSCBQu0ZMkS3XnnndZyitet1q1bW8eDFSv5vpakevXqKSsry2uDdyaXfDjd/7p58+YKCgrS2rVrrWmKtyvlUdx7VPxFY82aNbrkkkt099136/zzz9fixYvVsmVLtWrVytre9erVS26322t7d/w8CwoKtH79erVu3Vpr1qyxtm/Fy2jTpo2SkpL0yy+/6MCBA9Z2r2vXrvrnP/+pLVu2qGvXrlqzZo1SUlLUvHlzRUZGqlmzZtq9e7ccDofVFsHBwTp8+LBXW3To0EFHjx71CjctWrRQTEyMHA6HX9rzggsuUIsWLU7Yi+JwOKx1s02bNgoICFB+fr5atGihbt26qbCwUIcOHbLWzc2bNysnJ0cXXXSR3nzzTU2ZMkU//PCDvvjiCx04cEB5eXn6/fffrfbctm2b13bb7XZbl0Vo3ry5AgMDvXrHDxw4UGqbGxwcrNjY2JN+7rRp00Yul0v79u2TJK92L9kTdDLz5s1To0aNlJGR4fX5OmnSJM2ePbtM26fWrVtr165d1p4JSfrhhx908OBBtWnTRtKxnvqTvYYff/xR+/fv17PPPqvLLrtMCQkJpXqCyrK9bN26tQoKCrzWr/3792vz5s1WHb5SLcLTkiVLdODAAQ0ZMkTnnXee1+2mm27y2nX3xBNPaMWKFfr+++81ePBg1a1b1+t6OEFBQbr33nu1du1arV+/XoMHD9bFF19cpl0qbrdbY8aM0YMPPmh1iX711VfW8lu2bKmdO3fqrbfe0rZt2/Tyyy9b6blYkyZNtGPHDqWnp2vfvn3Kz88vtZz+/fvL7XZr0KBB+v7777Vy5Urde++9GjhwoNfB6b5w+PBhbdu2TW+++aY2bNigHTt26Pvvv1dgYKD++OMPazdpseKeg+HDh2vmzJl67bXXrG88V1xxhSRZ04wePdr6Fr9y5Uqv+bRs2VLvv/++FYL/7//+74x7bZYsWaIBAwZoyZIl2rJlizZv3qwXXnhB//rXv5SSkiJJio+Pl8Ph0JIlS7R3717r29qJDB8+XL/99pv69eundevWadu2bUpNTdWtt95a5qBz1VVXqXnz5ho0aJA2bNigNWvW6NFHH5X0v2+f9evXV0hIiHWQst0e1EOHDpXqMalbt66OHj2qqVOnavv27XrjjTc0ffp0r+maNGmivLw8rVixQvv27dPhw4fVqlUr9e/fX7fccovef/997dixQ19//bUmTJigpUuXlrmmxx9/XN9//722b9+un376Sd9++62mTp2qPn36KCAgQK+99pr69u2rVatWadOmTUpKSrLGmTNnjiRp2LBh+umnnzR69Ght3ry51EHR0rEP+71792rixInatm2bpk2bpo8++shW+0mn/1+Hh4dryJAhGj16tD799FNru1K8O62sDh8+rKysLGVlZSkjI0N33XWX3G63rr76aknH3g/ffPONUlNT9frrr2vfvn3KyspSSEiIta2rXbu2GjRoUOpQhWJOp1M9evTQnXfeqZSUFM2aNUs9e/aUy+XSqlWr9P7772vUqFG6/PLLrZAxb948LV++XK1bt9abb76p2rVrq1WrVmrZsqWWL1+uX3/9Vbm5ubrzzju1d+9excfHW20RERGhBQsWSDoWWoqKijR8+HBJ0pQpU7R06VKtW7dOqampmjFjhowxXu25YcMGSarw9tyyZYsee+yxk167qOS62aFDB23dulVz5sxRYGCgEhMTdeONN2rcuHFav369rrrqKgUHB2vv3r3atGmTlixZotatWys3N1cbN25UWFiYBg0apKZNm+rNN99UQECA13Y7NjZW2dnZWrp0qf7973+rZcuW2r9/v/bs2WOtW8dr0qSJIiIitG7dOt12223asGGD9uzZo/z8fO3bt0+1atXSqFGjrF6ibdu2lXpPncqMGTP0//7f/yv12TpkyBDt27dPy5YtO+08unfvrvPPP1/9+/fXt99+q6+//lq33HKLkpKS1KlTJ0nS+PHj9c9//lPjx49XZmamNm7cqOeee06S1LhxYwUHB1vbrQ8//LDUtZvKsg1v2bKlUlJSNHToUH3xxRfKyMjQgAEDdM4551ifBT5j6wgpP7nuuuvMtddee8Jha9euNZLMSy+9ZCSZxYsXm7Zt25rg4GBz0UUXmYyMDGvc4gNl33vvPdOsWTPjcrlM9+7dzS+//GKNU5ZLFTz11FMmPj7eBAUFmcaNG5tnnnnGGj569GhTp04dEx4ebvr27WsmT57sdXCux+MxN910k4mKivLJpQpKuu+++0od5Hc6jzzyiKlfv77p0KGDiYyMNKGhoebcc8811113nXWwX8naig/aa9KkiXUZgubNmxtJ5scff/Qap2vXriY8PNyEhYVZlzMoPqhzx44dplu3biYkJMTExcWZv/3tb6c9FfZktm3bZoYOHWpatWplQkJCTFRUlLnwwgutti32xBNPmNjYWONwOE56mmuxLVu2mBtuuME63TUhIcHcf//9pqio6KTTpaSkWPM15n+XKggODjYJCQlm8eLFRpJZtmyZNc7f//53ExcXZ5xOZ6lLFZR0/P920KBBpU7d1X9PXX/xxRdNgwYNTEhIiElOTjZz584tdaDlsGHDTJ06dbwuVXDkyBEzbtw406RJExMUFGQaNGhgbrjhBrNhwwZjzIkPNF+4cKE5fjNy8cUXm/DwcGse9957rzHGmAkTJph69eqZ3NxcU7t2bRMWFmaCgoJMvXr1THJyslm9erU1j8WLF1uXE7nsssvMzJkzS72GV1991cTFxZmwsDBzyy23mKeffvq0B4yfyf86NzfXDBgwwISGhpqYmBgzceJE26fWl/wf1a5d2yQlJZlPP/3UGsfj8ZjBgwebyMhIExgYaBo3bmweeuihUtuiyy+/3Gt7N2zYMJOUlGT9b/bs2WN69uxpXC6XqV27dqlLFRRr3769qV+/vrn11ltNnTp1jNvtNpLM5Zdfbow5duBySkqKCQwMNC6Xyzz66KPmlltuMT179rTaok6dOqZx48bWgdfF7+133nnHREREWK83ISHBXH311SYiIsKrPYtPJqjo9oyKijJ33XWXeeihh0zt2rVLXarAmP+tm3fffbdp3ry5Offcc01QUJCpU6eOqVevnrWtv+mmm0xQUJAJCgoy0dHRJiUlxWzfvt20b9/exMbGem23JZlmzZp5bbcHDhxomjRpYl1G4vHHHzeNGjUyAQEB1rrlcrms/4MxxqSlpZl27dqZoKAgI8m4XC7rUgXF74eioiJz2223WZedONF76kS++eYbr4O6j3fNNdeYG264wWr38l6q4L333jN/+tOfTHBwsKlbt6658cYbrWHz5883TZo0MS6XyyQmJpoPP/yw1Ak1ZdmGF1+qIDIy0toGnuhSBSWdaDt2Og5jKukKXBVs1apV6tatmw4cOHDSi5DNnj1b999/f5W6ynRV9eSTT2rBggXWt8NiJ2rnefPm6dZbb9WhQ4dOe1xYTbZmzRpdeuml2rp1q9fBijVNXl6ezjnnHM2aNUs33nhjmaYpy/sbACpLoL8LQNWSl5enn3/+WX/729/01FNPnXS8tLQ0JSQkKCMjQ2PGjNGf//xngtNxFi5cqPDwcLVs2VJbt27Vfffdpy5dutTY4FRUVKR9+/Zp0qRJioqKUu/evf1dEgCckWpxzBPs+fzzz71OvT7+dir33HOPOnbsqK5du+q222476Xh33nmnWrdurREjRqhPnz56/fXXff0yLPPmzTvpa2nbtm2FLbe8cnNzNXz4cCUkJGjw4MG68MILtWjRIn+X5Tc7d+5UTEyM5s+fr5kzZ1qnRVdn5XmvoTTa0/eGDRt20vYcNmyYv8urts6a3Xb4nz/++MO6yveJtGjRohKrKb/c3Fyvs9ZKCgoKUnx8fCVXBBxztr3X/I329L1ff/1VOTk5JxwWERFR6ppSKBvCEwAAgA3stgMAALCB8AQAAGAD4QkAAMAGwhMAAIANhCcAAAAbCE8AAAA2EJ4AAABsIDwBAADY8P8BkMjOWeHZIiYAAAAASUVORK5CYII="},"metadata":{}}]},{"cell_type":"code","source":"# Define the min-max scaling function\ndef min_max_scaling(column):\n min_val = column.min()\n max_val = column.max()\n return (column - min_val) / (max_val - min_val)\n\nTransformed_df = df\n\nTransformed_df['Signal_Strength'] = min_max_scaling(df['Signal_Strength'])\nTransformed_df['Latency'] = min_max_scaling(df['Latency'])\nTransformed_df['Required_Bandwidth'] = min_max_scaling(df['Required_Bandwidth'])\nTransformed_df['Allocated_Bandwidth'] = min_max_scaling(df['Allocated_Bandwidth'])\nTransformed_df['Resource_Allocation'] = min_max_scaling(df['Resource_Allocation'])\nTransformed_df['Application_Type'] = min_max_scaling(df['Application_Type'])\n\nTransformed_df.drop('Timestamp', axis=1, inplace=True)\n\nplt.figure(figsize=(12,6))\nsns.boxplot(data=Transformed_df)\nplt.show()\n\n# Thus, all columns data now comes in same range","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:58.817481Z","iopub.execute_input":"2023-09-04T15:17:58.817832Z","iopub.status.idle":"2023-09-04T15:17:59.082661Z","shell.execute_reply.started":"2023-09-04T15:17:58.817803Z","shell.execute_reply":"2023-09-04T15:17:59.081478Z"},"trusted":true},"execution_count":223,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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387 entries, 0 to 399\nData columns (total 6 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 Application_Type 387 non-null float64\n 1 Signal_Strength 387 non-null float64\n 2 Latency 387 non-null float64\n 3 Required_Bandwidth 387 non-null float64\n 4 Allocated_Bandwidth 387 non-null float64\n 5 Resource_Allocation 387 non-null float64\ndtypes: float64(6)\nmemory usage: 29.3 KB\n","output_type":"stream"}]},{"cell_type":"code","source":"Transformed_df.describe()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.099480Z","iopub.execute_input":"2023-09-04T15:17:59.099886Z","iopub.status.idle":"2023-09-04T15:17:59.131215Z","shell.execute_reply.started":"2023-09-04T15:17:59.099855Z","shell.execute_reply":"2023-09-04T15:17:59.130029Z"},"trusted":true},"execution_count":225,"outputs":[{"execution_count":225,"output_type":"execute_result","data":{"text/plain":" Application_Type Signal_Strength Latency Required_Bandwidth \\\ncount 387.000000 387.000000 387.000000 387.000000 \nmean 0.532587 0.520096 0.404227 0.386077 \nstd 0.337124 0.249585 0.221440 0.273194 \nmin 0.000000 0.000000 0.000000 0.000000 \n25% 0.333333 0.313253 0.269231 0.185695 \n50% 0.555556 0.493976 0.397436 0.310728 \n75% 0.777778 0.722892 0.564103 0.531751 \nmax 1.000000 1.000000 1.000000 1.000000 \n\n Allocated_Bandwidth Resource_Allocation \ncount 387.000000 387.000000 \nmean 0.390511 0.567368 \nstd 0.277136 0.257148 \nmin 0.000000 0.000000 \n25% 0.177892 0.428571 \n50% 0.328017 0.428571 \n75% 0.536625 0.714286 \nmax 1.000000 1.000000 ","text/html":"
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Application_TypeSignal_StrengthLatencyRequired_BandwidthAllocated_BandwidthResource_Allocation
count387.000000387.000000387.000000387.000000387.000000387.000000
mean0.5325870.5200960.4042270.3860770.3905110.567368
std0.3371240.2495850.2214400.2731940.2771360.257148
min0.0000000.0000000.0000000.0000000.0000000.000000
25%0.3333330.3132530.2692310.1856950.1778920.428571
50%0.5555560.4939760.3974360.3107280.3280170.428571
75%0.7777780.7228920.5641030.5317510.5366250.714286
max1.0000001.0000001.0000001.0000001.0000001.000000
\n
"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Split the DataFrame :**","metadata":{}},{"cell_type":"code","source":"X = Transformed_df.drop('Resource_Allocation', axis=1)\nY = Transformed_df['Resource_Allocation']","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.132883Z","iopub.execute_input":"2023-09-04T15:17:59.133865Z","iopub.status.idle":"2023-09-04T15:17:59.141119Z","shell.execute_reply.started":"2023-09-04T15:17:59.133821Z","shell.execute_reply":"2023-09-04T15:17:59.140076Z"},"trusted":true},"execution_count":226,"outputs":[]},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split\n\nx_train,x_test,y_train,y_test = train_test_split(X, Y, test_size=0.20, random_state=42)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.142521Z","iopub.execute_input":"2023-09-04T15:17:59.143408Z","iopub.status.idle":"2023-09-04T15:17:59.158897Z","shell.execute_reply.started":"2023-09-04T15:17:59.143376Z","shell.execute_reply":"2023-09-04T15:17:59.157706Z"},"trusted":true},"execution_count":227,"outputs":[]},{"cell_type":"code","source":"x_train.shape,x_test.shape,y_train.shape,y_test.shape","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.160880Z","iopub.execute_input":"2023-09-04T15:17:59.161363Z","iopub.status.idle":"2023-09-04T15:17:59.171505Z","shell.execute_reply.started":"2023-09-04T15:17:59.161324Z","shell.execute_reply":"2023-09-04T15:17:59.170705Z"},"trusted":true},"execution_count":228,"outputs":[{"execution_count":228,"output_type":"execute_result","data":{"text/plain":"((309, 5), (78, 5), (309,), (78,))"},"metadata":{}}]},{"cell_type":"markdown","source":"# **Linear Regression Model :**","metadata":{}},{"cell_type":"markdown","source":"> **Create and Train the Model :**","metadata":{}},{"cell_type":"code","source":"from sklearn.linear_model import LinearRegression","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.172972Z","iopub.execute_input":"2023-09-04T15:17:59.174008Z","iopub.status.idle":"2023-09-04T15:17:59.181447Z","shell.execute_reply.started":"2023-09-04T15:17:59.173967Z","shell.execute_reply":"2023-09-04T15:17:59.180378Z"},"trusted":true},"execution_count":229,"outputs":[]},{"cell_type":"code","source":"lin_regressor = LinearRegression()\nlin_regressor.fit(x_train,y_train)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.182989Z","iopub.execute_input":"2023-09-04T15:17:59.184233Z","iopub.status.idle":"2023-09-04T15:17:59.199960Z","shell.execute_reply.started":"2023-09-04T15:17:59.184199Z","shell.execute_reply":"2023-09-04T15:17:59.198768Z"},"trusted":true},"execution_count":230,"outputs":[{"execution_count":230,"output_type":"execute_result","data":{"text/plain":"LinearRegression()","text/html":"
LinearRegression()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Predict Test Set Results :**","metadata":{}},{"cell_type":"code","source":"lin_regressor_y_pred = lin_regressor.predict(x_test)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.201553Z","iopub.execute_input":"2023-09-04T15:17:59.201930Z","iopub.status.idle":"2023-09-04T15:17:59.209875Z","shell.execute_reply.started":"2023-09-04T15:17:59.201899Z","shell.execute_reply":"2023-09-04T15:17:59.208934Z"},"trusted":true},"execution_count":231,"outputs":[]},{"cell_type":"markdown","source":"> **Evaluation of Model Performance :**","metadata":{}},{"cell_type":"code","source":"from sklearn.metrics import r2_score, mean_squared_error","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.211417Z","iopub.execute_input":"2023-09-04T15:17:59.212147Z","iopub.status.idle":"2023-09-04T15:17:59.219651Z","shell.execute_reply.started":"2023-09-04T15:17:59.212105Z","shell.execute_reply":"2023-09-04T15:17:59.218795Z"},"trusted":true},"execution_count":232,"outputs":[]},{"cell_type":"code","source":"lin_regressor_r2 = r2_score(y_test, lin_regressor_y_pred)\nlin_regressor_r2","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.220710Z","iopub.execute_input":"2023-09-04T15:17:59.221707Z","iopub.status.idle":"2023-09-04T15:17:59.233664Z","shell.execute_reply.started":"2023-09-04T15:17:59.221677Z","shell.execute_reply":"2023-09-04T15:17:59.232673Z"},"trusted":true},"execution_count":233,"outputs":[{"execution_count":233,"output_type":"execute_result","data":{"text/plain":"-0.048720141610214984"},"metadata":{}}]},{"cell_type":"code","source":"lin_regressor_mse = mean_squared_error(y_test, lin_regressor_y_pred)\nlin_regressor_mse","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.235141Z","iopub.execute_input":"2023-09-04T15:17:59.235446Z","iopub.status.idle":"2023-09-04T15:17:59.246134Z","shell.execute_reply.started":"2023-09-04T15:17:59.235419Z","shell.execute_reply":"2023-09-04T15:17:59.244982Z"},"trusted":true},"execution_count":234,"outputs":[{"execution_count":234,"output_type":"execute_result","data":{"text/plain":"0.07650919226033008"},"metadata":{}}]},{"cell_type":"code","source":"lin_regressor_rmse = np.sqrt(lin_regressor_mse)\nlin_regressor_rmse","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.247570Z","iopub.execute_input":"2023-09-04T15:17:59.248126Z","iopub.status.idle":"2023-09-04T15:17:59.259130Z","shell.execute_reply.started":"2023-09-04T15:17:59.248095Z","shell.execute_reply":"2023-09-04T15:17:59.258342Z"},"trusted":true},"execution_count":235,"outputs":[{"execution_count":235,"output_type":"execute_result","data":{"text/plain":"0.2766029505633121"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Visualize the Results of the Prediction :**","metadata":{}},{"cell_type":"code","source":"plt.scatter(y_test, lin_regressor_y_pred)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.260192Z","iopub.execute_input":"2023-09-04T15:17:59.261076Z","iopub.status.idle":"2023-09-04T15:17:59.462396Z","shell.execute_reply.started":"2023-09-04T15:17:59.261045Z","shell.execute_reply":"2023-09-04T15:17:59.460970Z"},"trusted":true},"execution_count":236,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"# Scatter Plots of each feature vs predicted value with regression line\n\nlin_regressor_plot = x_test\nlin_regressor_plot['Y_Predicted'] = lin_regressor_y_pred\n\nsns.lmplot(x='Signal_Strength', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Latency', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Required_Bandwidth', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Allocated_Bandwidth', y='Y_Predicted', data=lin_regressor_plot)\n\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:17:59.463807Z","iopub.execute_input":"2023-09-04T15:17:59.464158Z","iopub.status.idle":"2023-09-04T15:18:01.279321Z","shell.execute_reply.started":"2023-09-04T15:17:59.464127Z","shell.execute_reply":"2023-09-04T15:18:01.278245Z"},"trusted":true},"execution_count":237,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"markdown","source":"# **SVM Regression Model :**","metadata":{}},{"cell_type":"markdown","source":"> **Create and Train the Model :**","metadata":{}},{"cell_type":"code","source":"from sklearn.svm import SVR","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.280850Z","iopub.execute_input":"2023-09-04T15:18:01.281156Z","iopub.status.idle":"2023-09-04T15:18:01.286258Z","shell.execute_reply.started":"2023-09-04T15:18:01.281128Z","shell.execute_reply":"2023-09-04T15:18:01.285179Z"},"trusted":true},"execution_count":238,"outputs":[]},{"cell_type":"code","source":"svr = SVR(kernel='poly')\nsvr.fit(x_train, y_train)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.293699Z","iopub.execute_input":"2023-09-04T15:18:01.294076Z","iopub.status.idle":"2023-09-04T15:18:01.353597Z","shell.execute_reply.started":"2023-09-04T15:18:01.294045Z","shell.execute_reply":"2023-09-04T15:18:01.352791Z"},"trusted":true},"execution_count":239,"outputs":[{"execution_count":239,"output_type":"execute_result","data":{"text/plain":"SVR(kernel='poly')","text/html":"
SVR(kernel='poly')
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Predict Test Set Results :**","metadata":{}},{"cell_type":"code","source":"x_test.drop('Y_Predicted', axis=1, inplace=True)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.355097Z","iopub.execute_input":"2023-09-04T15:18:01.355785Z","iopub.status.idle":"2023-09-04T15:18:01.362545Z","shell.execute_reply.started":"2023-09-04T15:18:01.355743Z","shell.execute_reply":"2023-09-04T15:18:01.361419Z"},"trusted":true},"execution_count":240,"outputs":[]},{"cell_type":"code","source":"svr_y_pred = svr.predict(x_test)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.365732Z","iopub.execute_input":"2023-09-04T15:18:01.366275Z","iopub.status.idle":"2023-09-04T15:18:01.377658Z","shell.execute_reply.started":"2023-09-04T15:18:01.366222Z","shell.execute_reply":"2023-09-04T15:18:01.376649Z"},"trusted":true},"execution_count":241,"outputs":[]},{"cell_type":"markdown","source":"> **Evaluation of Model Performance :**","metadata":{}},{"cell_type":"code","source":"svr_r2 = r2_score(y_test, svr_y_pred)\nsvr_r2","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.379130Z","iopub.execute_input":"2023-09-04T15:18:01.379485Z","iopub.status.idle":"2023-09-04T15:18:01.394103Z","shell.execute_reply.started":"2023-09-04T15:18:01.379456Z","shell.execute_reply":"2023-09-04T15:18:01.392822Z"},"trusted":true},"execution_count":242,"outputs":[{"execution_count":242,"output_type":"execute_result","data":{"text/plain":"0.5166550618405741"},"metadata":{}}]},{"cell_type":"code","source":"svr_mse = mean_squared_error(y_test, svr_y_pred)\nsvr_mse","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.395950Z","iopub.execute_input":"2023-09-04T15:18:01.396493Z","iopub.status.idle":"2023-09-04T15:18:01.408268Z","shell.execute_reply.started":"2023-09-04T15:18:01.396458Z","shell.execute_reply":"2023-09-04T15:18:01.407122Z"},"trusted":true},"execution_count":243,"outputs":[{"execution_count":243,"output_type":"execute_result","data":{"text/plain":"0.035262344389530756"},"metadata":{}}]},{"cell_type":"code","source":"svr_rmse = np.sqrt(svr_mse)\nsvr_rmse","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.409967Z","iopub.execute_input":"2023-09-04T15:18:01.410410Z","iopub.status.idle":"2023-09-04T15:18:01.421736Z","shell.execute_reply.started":"2023-09-04T15:18:01.410367Z","shell.execute_reply":"2023-09-04T15:18:01.420510Z"},"trusted":true},"execution_count":244,"outputs":[{"execution_count":244,"output_type":"execute_result","data":{"text/plain":"0.1877827052460656"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Visualize the Results of the Prediction :**","metadata":{}},{"cell_type":"code","source":"# Plot Actual vs Predicted Values\n\nplt.scatter(y_test, svr_y_pred)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.423941Z","iopub.execute_input":"2023-09-04T15:18:01.425216Z","iopub.status.idle":"2023-09-04T15:18:01.623369Z","shell.execute_reply.started":"2023-09-04T15:18:01.425173Z","shell.execute_reply":"2023-09-04T15:18:01.621981Z"},"trusted":true},"execution_count":245,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"# Scatter Plots of each feature vs predicted value with regression line\n\nlin_regressor_plot = x_test\nlin_regressor_plot['Y_Predicted'] = svr_y_pred\n\nsns.lmplot(x='Signal_Strength', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Latency', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Required_Bandwidth', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Allocated_Bandwidth', y='Y_Predicted', data=lin_regressor_plot)\n\nplt.tight_layout()\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:01.626028Z","iopub.execute_input":"2023-09-04T15:18:01.626467Z","iopub.status.idle":"2023-09-04T15:18:03.428474Z","shell.execute_reply.started":"2023-09-04T15:18:01.626423Z","shell.execute_reply":"2023-09-04T15:18:03.427563Z"},"trusted":true},"execution_count":246,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/tmp/ipykernel_32/4005064551.py:14: UserWarning: The figure layout has changed to tight\n plt.tight_layout()\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
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qVUwaAmopTF0qCUClhClIhSHkuDUjJjZTIiSnksDUrJjEPfREREOsagJiIi0jEGNRERkY4xqImIiHSMQU1ERKRjDGoiIiIdY1ATERHpGIOaiIhIxxjUREREOhZWZbJf/epXYT/hD3/4wz43hoiIiIKFVev7rLPOCvr8+PHjcDqdyMnJAQA0NzfDarWioKAA+/fvj0lDo4W1vomIKJmENfR94MCBwMejjz6KMWPGoKqqCk1NTWhqakJVVRUuuOACPPLII7FuLxER0YAS8elZ5eXlePPNNzF27Nig27dv347/+I//wIEDB6LawGhjj5pIf3i6FVHPIj49q7a2Fl6vt9vtqqqivr4+Ko0iooFjS3UjVm2uQU2DAx5VwKhIKC/IwNwp5Twvmgh9WPV91VVX4Y477sCOHTsCt23fvh1z587F1KlTo9o4IkptW6obsXjtblTV2pFuNqAg04x0swFVtS1YvHY3tlQ3JrqJRAkXcVC/8MILKCoqwvjx42E2m2E2mzFhwgQUFhbi+eefj0UbiSgFaZrAqs01cLi8KMqywGJUIMsSLEYFRVlmOFwqVm2ugaZFNDtHlHIiHvoePHgw1q9fj3379uGrr74CAJxzzjkYMWJE1BtHRKlrzzE7ahocyLWaIEnB89GSJCHHakRNgwN7jtlRMSQ7Qa0kSryIg9pv6NChEEKgvLwcBkOfn4Z0jot8KFaanG54VAGTEnpgz6zIsGkCTU53nFtGpC8RJ6zT6cTdd9+Nl19+GQCwb98+DBs2DHfffTdKS0uxcOHCqDeSEqO/i3wY8nQ6eVYTjIoEt6rBIivdvu5SNRhlCXlWUwJaR6QfEc9RL1q0CJ9//jk2bdoEi8USuH3q1Kl4/fXXo9o4Spz+LvLZUt2I2S9uwx2/+wz3/fFz3PG7zzD7xW1cHEQBo0qyUF6QgZNOD7ruEhVCoNnpQXlBBkaVcBslDWwRB/W6devwzDPP4JJLLgmaVxo1ahRqamr61IiVK1di6NChsFgsmDhxIrZt23ba+69YsQJnn3020tLSUFZWhnvvvRft7e19+t7UXX8X+XAlL4VDliXMnVKODLOCOrsLbR4VmibQ5lFRZ3chw6xg7pRyjsLQgBdxUB8/fhwFBQXdbm9tbe22ICQcr7/+OubPn4+lS5dix44dGD16NKZNm4aGhoaQ93/11VexcOFCLF26FFVVVfjNb36D119/HYsXL474e1NokSzy6YoreSkSk4fnY9mNFRhZnAmny4sGhwtOlxcjizOx7MYK7qMmQh/mqMePH493330Xd999NwAEXsiff/55TJo0KeIGPPnkk7j99tsxZ84cAMDq1avx7rvv4oUXXgg5371lyxZcfPHFmDlzJgDforabb74Zf//73yP+3hRafxb5RGMlL+e2B5bJw/Nx0bBB/Dsn6kHEQb1s2TJcd911+PLLL+H1evHLX/4SX375JbZs2YLNmzdH9Fxutxvbt2/HokWLArfJsoypU6di69atIR8zefJkvPLKK9i2bRsmTJiA/fv3Y/369bjllltC3t/lcsHlcgU+t9u79wIpWH8W+fR3JS+rVA1MsixxCxZRDyIe+r7kkkuwa9cueL1eVFRU4K9//SsKCgqwdetWjBs3LqLnamxshKqqKCwsDLq9sLAQdXV1IR8zc+ZMPPzww7jkkktgNBpRXl6Oyy+/vMeh7+XLlyM7OzvwUVZWFlEbB6L+LPLpHPKhnC7kObdNRNRdxEEN+A7mWLNmDbZt24Yvv/wSr7zyCioqKqLdtpA2bdqEZcuW4dlnn8WOHTvw9ttv49133+3x5K5FixbBZrMFPg4fPhyXdiaz/izy6WvIc26biCi0iINaUZSQC71OnDgBRek+THo6+fn5UBSl22Ee9fX1KCoqCvmYBx98ELfccgtuu+02VFRU4MYbb8SyZcuwfPlyaFr3XpzZbEZWVlbQB/Wur4t8+hry/VnARkSUyiKeo+7pVEyXywWTKbLCBCaTCePGjcPGjRsxffp0AICmadi4cSPuuuuukI9xOp2Q5eD3F/43CBGe2Em96OsiH3/I++eabZqAUZYwsjizx7lmVqkiIgot7KD+1a9+BcDXu3n++eeRkZER+Jqqqvj4449xzjnnRNyA+fPnY/bs2Rg/fjwmTJiAFStWoLW1NbAKfNasWSgtLcXy5csBAJWVlXjyyScxduxYTJw4EdXV1XjwwQdRWVkZcY+eetfXRT6RhjyrVBERhRZ2UD/11FMAfL3W1atXB4WiyWTC0KFDsXr16ogbMGPGDBw/fhxLlixBXV0dxowZgw0bNgQWmB06dCioB/3AAw9AkiQ88MADOHr0KAYPHozKyko8+uijEX9viq1IQt4/t11V24KiLDlo+Ns/tz2yOJNVqohowJFEhOPFV1xxBd5++23k5ubGqk0xZbfbkZ2dDZvNxvlqnfGv+na4VORYjTArMlyqhmanBxlmhQUwkpTXq+HPX9TiaLMTpTlWVJ5fDIOhT+tYiQakiIM62TGo9S1oH3XH3Db3USevNR/XYOWmGrS0eaDBt3o1M82IeZeX4/bLyhPdPKKkEHFQf/vb38aECROwYMGCoNsff/xx/OMf/8Abb7wR1QZGG4Na/1iZLDWs+bgGP9uwF6omYFAkyBKgCcCrCiiyhAXXns2wJgpDxEE9ePBgfPjhh932Te/evRtTp07tttVKbxjURLHn9WoYv+wD2JwemAwSZOnUULcmNLi9AtlWIz5bPJXD4ES9iPg3xOFwhNyGZTQaWZ6TiAAAf/6iFi1tno6edPDLjCzJMCgSWto8+PMXtQlqIVHyiDioKyoqQp47/dprr+Hcc8+NSqOIKLkdbXb65qR7mLGQJUB03I8oGbi8KmxtnoR874gLnjz44IP493//d9TU1ODKK68EAGzcuBF/+MMfdD8/TUTxUZpjhQzfnHSosNYEIHXcj0iPvKqGVreKNreKdo8KTQhIkoTsNGPc2xJxUFdWVmLdunVYtmwZ3nzzTaSlpeH888/HBx98gClTpsSijUSUZCrPL8ZD7+yBzemBLGnd5qi9qm+OuvL84gS2kiiYP5xbXV60e9RENyeA27OIKEi0Vt1z1Tclg0jCWZIknJWfHqeWnRJxj5qIkldvIRzN88D9IezfR63CN9ydbeU+akocTRNo9/qGtNs8Ktze0Efy6klYPeq8vDzs27cP+fn5yM3N7Xa6UWdNTU1RbWC0sUdNA1VvIXyqMpwXuVYTTIoMt6rhZD8rw7EyGSWaR9XgdKtwur1o92h9PsBJ1z3qp556CpmZmQCAFStWxLI9RBQDPYVwVW0LFq/djZ9OPw+//nh/4Dxw/5txi6ygKEtGnd2FVZtrcNGwQREPgxsMMm68oDQWPxZRj7yqhlaXCofbC5eO5pv7gnPURHGQyGprmiYw+8VtqKq1B4Uw4DvwpM7uwpDcNDTY25FuNsBi7H56WZtHhdPlxa9vGd+n09SI4sGranB6fPPNbe7oh7Oue9SRFDJh+BEFi+a8b1/sOWZHTYMDuVZTt2krSZKQYzXi0IlWCAC5PRwjyvPASa/aPb7tU61uNel7zj0JK6hzcnJOOy/dmaqm5oUi6ovehpxjeSKYvxe/eV8D2jy+E8lCMSsyNACKxPPASd+EEHB5Nbi8Gto9vgVh2gAYFA4rqD/66KPAfx88eBALFy7ErbfeikmTJgEAtm7dipdffhnLly+PTSuJkpCmCazaXBOTed/edO7FO90qWto9aPdoKMq2IMMc/GvvUjWkGWQUZqfhyMk2ngdOuuH2anB51Y4/fR8DbLYWQJhB3bmQycMPP4wnn3wSN998c+C2G264ARUVFXjuuecwe/bs6LeSKAmFM+Rc0+DAnmP2qM77du3F56QZcdCroc2j4kiTE0PyrIGw7hzCd1w2DA+s+yfq7K6Q54HPnVKetKeY8UQ2fdM0AbfqC2K3V4Nb9f05EEM5lIj3UW/duhWrV6/udvv48eNx2223RaVRRKmgyemGRxUwKaG3IsVi3renXnxhtgVHTzrhUQXqbO04K98KtyqCQnjy8Hwsu7Ei0BO3dZwHPrI4M6nPA0/0GgHqzr+Xud2jBfYyM5R7FnFQl5WVYc2aNXj88ceDbn/++edRVlYWtYYRJbs8qwlGJb7zvj314jPMBpTmWlFna4fbq6LW1o40o9IthCcPz8dFwwalTO8zkWsE6BQhRCCUGcyRizion3rqKXz729/GX/7yF0ycOBEAsG3bNnz99dd46623ot5AomQ1qiQL5QUZqKptidu87+l68RlmA84aZMUxezu+d8lZmDKiIGQIy7KUEluwErlGYKDzL/pq7wjm/hQZoT4cc3n99ddj3759qKysRFNTE5qamlBZWYl9+/bh+uuvj0UbiZKSLEuYO6UcGWYFdXYX2jwqNE2gzaOizu6Kybxv5158KG5NwGpUMGVEASqGZKd0QEWyRoD6z+VVYXN6UGdrx79OOHGsuQ1NrW60uVWGdD/1qdZ3WVkZli1bFu22EKWceM/7JqIXr1eJWCMwkKgdbzqdbi/a3Rq8mv5rZierPgX13/72N/z617/G/v378cYbb6C0tBS/+93vcNZZZ+GSSy6JdhuJklq0531Pt4LZ34tfvHZ3Sq7ejkQi1ggMBG0d2/1a2VOOm4iD+q233sItt9yC7373u9ixYwdcLhcAwGazYdmyZVi/fn3UG0mU7KI177uluhHPbqrGV3Ut8HgFjAYJ5xRl4s7LhwctCEvF1duR4uhC9Pirf7W0e+HpYVqFYifiWt9jx47Fvffei1mzZiEzMxOff/45hg0bhp07d+K6665DXV1drNoaFaz1TclqS3Uj7v3jLjQ53NAEICAgwXfOc16GCU/dNCYohLl3uPOqbzXk6AJXfYfm7th3P5Cqf4VD17W+O9u7dy8uu+yybrdnZ2ejubk5Gm0ioi40TWD5X6rQ0OJC8GumgCqAhhYXlv+lCv8775KgYfBUWL3dHxxdCI8QouMYSF8w9zTfrAmB6vpW2NrdyLaYMLwwHXKY5aWp7yIO6qKiIlRXV2Po0KFBt3/yyScYNmxYtNpFRJ3sPmrDV7UtgZDu/NIoAAgBfFXbgt1HbRhdlpOAFupXqu0NjxZNE3B2nIrmDKPXvPPQSby67TAOn2iFp+MNT9mgdMycUIaxZ+TGqdUDU8RBffvtt+Oee+7BCy+8AEmScOzYMWzduhX33XcfHnzwwVi0kWjA23HoJDya74VUCvyfjyR8Ye3RBHYcOsmgDoGjCz6aJtDq9gZ6z+HOfO48dBJPvr8PTreKLIsRWYoEjyqw/7gDT76/D/OvHsGwjqGIg3rhwoXQNA1XXXUVnE4nLrvsMpjNZtx33324++67Y9FGogGvztZ+6pOuHUEJvqTuej8a8DpXBGv3qH061EITAq9uOwynW0V+hglSxz9As0FCfoYJjQ43Xt12GKPLcjgMHiMRBbWqqvj0008xb948/PjHP0Z1dTUcDgfOPfdcZGRkxKqNRANecZYlqvej1OX2amhzq3B6vFGpCFZd34rDJ1qRZTEGQtpPgoRMixGHT7Siur4VI4qYA7EQUVArioJrrrkGVVVVyMnJwbnnnhurdhFRJ2PPzIVRluDRBIToNPwtAp1pGGUJY8/k8ONA1OZW0er2os2tRn37lK3dDY8mkKWE7i2bFAktQsDWzsIxsRJxCdHzzjsP+/fvj0VbiKgHFaXZOKc4E/71T/4FZP6QliXgnOJMVJRyHnYg0DQBh8uLhpZ2/OtEK2ptbbC3eWKyxznbYvK9SVRD98zdqoBRkpBtYeGYWIk4qH/605/ivvvuwzvvvIPa2lrY7fagDyKKPlmWsOi6kRicaYZRkaBIvv3TiiTBqEgYnGnGoutGDviVzKnMo2qwOT2otbXhX01ONNjb4Wj3QtViu8d5eGE6ygalw97ugUDw9xIQaGn3oGxQOoYXxn9/8UARccETWT6V7V0r/UiSBFVVo9e6GGDBE0pmQZXJOs5W7lqZjFJD54Vgra7EVgTrvOo702KESZHgVn0hbTUpA2bVd6IKnkQc1Js3bz7t16dMmdKvBsUag5r0oq+Vw1hxLDVp2qmjIdu9+jsaMmgftfANdw+0fdRJEdRCCFRXV8PtduPss8+GwdCnMz0SikFNerClujFQLcvfMy4vyGC1rAFC0wTcqgaXV4O7I5xj1WOOZjWxgV6ZTPdBfeDAAdxwww348ssvAQBDhgzBW2+9hfHjx8e0gdHGoKZEO1V/2otcqwkmRYZb1XCS9adTmsurotUV32FsVhOLrkQFddiLyX784x/D6/XilVdewZtvvokhQ4bgjjvuiGXbiFKOpgms2lwDh8uLoiwLLEYFsizBYlRQlGWGw6Vi1eYaaDFeIJSsNE1g9xEbNu87jt1HbLq/Tu0eFSdb3Tjc5MTRk21odrrjGtJPvr8P+487kGYyYFC6CWkmQ6Ca2M5DJ+PSDuq/sMeuP/nkE7z55puB86YvuugiDBkyBK2trUhP52o/onDsOWZHTYMDuVZT0GJMwPduPcdqRE2DA3uO2VnysotkmC5wezW4vCraOk6divWK7J6wmlhqCTuoGxoa8I1vfCPweXFxMdLS0tDQ0ICzzjorJo0jSjVNTjc8qoBJCT2YZVZk2DSBJieLR3TW03RBVW0LFq/dnZDpAlUTQaU53X0ozxmJSOaHWU0sOhztXhxp9o2GHG1uw9HmdhxvceEHU8px7XlFcWtH2EEtSRIcDgfS0tICt8myjJaWlqD905z3JepZntUEoyLBrWqwyEq3r7tUDUZZQp6VxSP8uk4X+EciLLKCoiwZtbZ2PP7eXvzIq2FQhjnqq+D9q+wbW11INxpw5iAr3KoW1+1Skc41s5pY+Bwu76kgPtmGI81tOHrSiaPN7bC1eUI+5qs6uz6DWgiBESNGdLtt7Nixgf9Ohn3URIk0qiQL5QUZqKptQVGW3K0WQbPTg5HFmRhVwje8fqebLmjtOAVq95Fm3PvHXUgzKlEbDtc0gU17G/Dc3/bjwPFWuDveRMV7MVZfTq7qXE3MbOge1gOtmljXMD7a3IYjJ9twrLkNzT2E8ekcbGyNQSt7FnZQf/TRR7FsB9GAIMsS5k4px+K1u1FndyHHaoRZkeFSNTR3rPqeO6Wc+6I76Wm6wP/iqwpfzzbTYoDZoEQ0HC6EgFcT8KoCHk2DVxXwqhrcqoa/7z8RFJCZFkPcj3bs61yzv5rY/uOOoMcBp6qJDRuckVLVxFpd3qBe8bGOMD56sm9h7GcxyhiSY0VpbhpKc9Mwpiwn7m+kww7qSAuZPPbYY/jBD36AnJycSNtElNImD8/HshsrAgujbB1DmSOLM3W1MEovQk0XCCFwvKUdqhBQJAlCAkyK0rF6Xkad3YVVm2tw0bBBkGUJHtU3h+xVRWDY2qsKeLXQw9d6WYzV17lmWZIwc0IZnnx/Hxod7pDVxGZOKEu6hWSdw9g3Z3yqZ3zS2Y8wNsi+IM7xhfGQjj9Lc9KQl35qJCdR27NiVrFk2bJluOmmmxjURCFMHp6Pi4YNYoWxMISaLmj3+IqFKDKgaYDFqMBi8vW4JUlCdpoBX9e34G9fN+Ks/PQeA7knelmM1Z+55rFn5GL+1SMCc9stHdXEhg3O0PU+aqfbP0zdjqPNzkCv+GgUwrikI4RLctIwJPdUGA9K7z6toicxC2o9lb4j0iNZlrgFKwyhpgs8qgZNANAEFFlGfoYJmgZoQgscA+pSNdTZ21CWl9bbt+hGL4ux+jvXPPaMXIwuy9FdNbE2txroER892TFE3fF5U2vfr6k/jEtzfB9DOvWS9R7Gp5N8NUCJKKqSoXZ45+mC6voWOD0qhCZgMsjIzzTDpMjwdlqF3d/FUnpZjBWNuWZZkhKyBavNo+JYp4VbnYP5RD/C2GSQQwZxaU6a7xolaRifDoOaaADTexERrWOvcptHxRmDrHjohlHYV+fAyTY3Xt5yEPX2dqQZgxeZRWOxlF4WY+l9rrnNo+JYp17xsWb/9qb+h3FJtqXbfPGQXCsGZZgSPiIQbwxqogFKL0VEOq+8dqsavKoGryYCC8C68vcOTYoUswDTU0Ameq653RM8TB3Y3tTchhOOvoexUZGCesNDcjvmjnPSkJ9pHnBhfDphH8px7NgxlJSUhP3EmZmZ+PzzzzFs2LBe77ty5Ur8/Oc/R11dHUaPHo2nn34aEyZM6PH+zc3NuP/++/H222+jqakJZ555JlasWIHrr7++1+/FQzlooDjdkLamCcx+cRuqau1BRUQAX3DW2V0YWZyJl+dMiMowuNoRvL5A1uDpWHHtVUW/CofsPHQSr/79MPY3nhoRGJafgZkToxNgejraMZYnV7V39IyPNLfh2MlTveKjzW1o7GcY+8O366rqZAxj3a/6HjVqFFauXImZM2eGdf9LL700qIpZT15//XXMnz8fq1evxsSJE7FixQpMmzYNe/fuRUFBQbf7u91uXH311SgoKMCbb76J0tJS/Otf/+LqcqJOehvSjnbNcf/eY4/XF8CqEFA134dXFdBiurhUBP3R6T/6TU+Lsfo71+zyqDhma+9YRe0MWlXd7zDODl5J7Q/mwUkYxnoUdo/62WefxYIFC3Dttdfi17/+NfLy8qLSgIkTJ+LCCy/EM888AwDQNA1lZWW4++67sXDhwm73X716NX7+85/jq6++gtFo7PX5XS4XXC5X4HO73Y6ysjL2qCllhXOMpkcTuO+Pn6Mg0xyyx6xpAg0OF574zmhMGTEYgK+n7fKe2oPs6dQjTsThE10rdhk7KnbZO4amo1WQJJnOYHZ7NRztXOyj0z7jhhZX70/QA6MioTi7yxB1RygPzjBD0dniw1jRfY/6zjvvxHXXXYfvfe97OPfcc7FmzRpUVlb265u73W5s374dixYtCtwmyzKmTp2KrVu3hnzMn/70J0yaNAnz5s3D//7v/2Lw4MGYOXMmFixYAEXpXjt5+fLleOihh/rVTqJk0VtdbH8hkPuuOTtkzXEhBITwLRJSJECRJNTb2+H2xre2dW/iVZBEj+c5u70ajtnaQtSnbsPxFlefxxMMsoRi/wKuoC1OVgzOHDhhrEcRLSY766yz8OGHH+KZZ57Bv//7v2PkyJEwGIKfYseOHWE/X2NjI1RVRWFhYdDthYWF+Oqrr0I+Zv/+/fjwww/x3e9+F+vXr0d1dTXuvPNOeDweLF26tNv9Fy1ahPnz5wc+9/eoiVJRb0Pa2WkG3/YmtxdnDLJiX70DgzNMACQICPj+J3DS6cawwRkoyjaj1eVNzA9zGvEoSNKXGtvREiqM/b3jaIWxP4j9wVyQaWEY61TEq77/9a9/4e2330Zubi6+9a1vdQvqWNM0DQUFBXjuueegKArGjRuHo0eP4uc//3nIoDabzTCbzXFtI1GiNLa64PZqyLZIUDXh6yEDEB0BLAFoVzUcanLiO+OG4Mn396GhxaW7bT+9iXVBknj02N1eDbW27r3io81taLD3PYwVfxh3WVFdmpOGwiyGcTKKKGXXrFmD//7v/8bUqVOxZ88eDB48uF/fPD8/H4qioL6+Puj2+vp6FBWFPkKsuLgYRqMxaJh75MiRqKurg9vthsk0ME6DoYHDPxzt1XyLsrSO7Uya5vtT1URgNbXLrUGWAKdHhdnQ/czrzoU6RhRlJGWJSSD2BUmi1WP3qBpqm9t9Zxo3t3dsb/L9d0NLO/o6tR8Uxp16xSU5aShiGKecsIP62muvxbZt2/DMM89g1qxZUfnmJpMJ48aNw8aNGzF9+nQAvh7zxo0bcdddd4V8zMUXX4xXX30VmqZBln0vRPv27UNxcTFDOsVoWs+rhf23+r/s79T4X54k6dTLq6/SpAj0Kv2P6fx55+/iX18pAAgNUMWpgOzWzZF8L9yS5PveiixBkiTfn/Ct1O3c4fI9T0d7NN+fgefXAK+mQev4nn0pwxtpoQ49rWqORKwLkkTSY/eoGmpt7adOberUO+5PGMsSfAu4utanzklDUTbDON40IVBT78ChJmfcK/iFHdSqquKLL77AkCFDotqA+fPnY/bs2Rg/fjwmTJiAFStWoLW1FXPmzAEAzJo1C6WlpVi+fDkAYO7cuXjmmWdwzz334O6778bXX3+NZcuW4Yc//GFU2xUup9sLl0fr9kLfebix43/dgiHUC7Hsf5GXENaLZTiv5SKSQbTT3LWnL4Xbhs455+8ldn4Ofzs1wVrxkeq8MvnSb+SjttkZdqGORJWY7I9YFyTp2mMXQsDT6eStNo8Gt1fFz9/bi6ZWd7/CuCjb0rGdyYrSHH81LisKs8wwKN1HRSj+Oi8qFJDiXsEv7KB+//33Y9KAGTNm4Pjx41iyZAnq6uowZswYbNiwIbDA7NChQ4GeMwCUlZXhvffew7333ovzzz8fpaWluOeee7BgwYKYtK83bW4Vtn6cdUrUX6FWJudYjcgwA81OT1INaUci2hW7vP6ecceiLSFJONrcBgmAp4ckDmf/sT+Mg+pT+3vGWRaGsc51XVSYYTbEvYJf2PuoU0W0K5OdcLgY1JQwp9tLnGZScNP4MhRnW5JmSLsvItnn7FU11NnbT9Wl7nRYRJ2tf8PUhVmW4D3GOaeGqY0M46SkCYEFb+0+NcUiSTAbTp2JHu0Kfj1hrW+iJBXOyuS/fd2In327IikDOtwA7jp0r2oCR22hD4qotbX1OYx93wvIMBtwXmk2xpTlBM0ZM4xTz2kXFfahgl9fMaiJklQ89hJHQ18qe/VWaETVBOrt7cFHKHb8WWtr73OlNH/P2F+f2ne2sQVeFTAqwKB0S8qOTFB3vS0qNCsybJpAkzO255IzqImiLF4lJ2O9lzga+lLZyz+c3+rywmoywKAItHs0/POoDYvX2pBlMeCk0wNvH8NYAlCQZT61gKsjjIfkWFGUbYEpxLY2Gph62wboUjUYZQl51tjuOGJQE0VRPEtOxnovcX+FU9nr/CE5aGhpD/SGD59sw8aqBrS0e6AJoLmte1W042Es4JIADM40Bx0S4Z87Ls5OYxhTWE67DVAINDs9GFmciVElsT03gkFNUZFMBxfESrxLTsZ6L3F/dJ4/H5RuhKr56od7vL794Q12Fxav/WegWEtfdA3jzsU/ShjGFAWhtgEaZRkuVUNzxyE3c6eUx3w/NYOaTiucANbjwQXxFq9DIjqL9V7iSKiawPEWV2DO+J9Hbdh9pNnXK3Z6Qu/BDzOgDbIEoyLDpEgwKDLavSruuGwYrjm3iGFMMdd1G2CbR4VRljCyOFN/+6gp9XUN5RaXG6/948hpAziRBxfoSaIWdkV7L/HpaEKgocUVVHnLv4jrmK0NHrXvy6kLMs0oyUlDhtmAnYdOwmpSYDUpMCpy0BuNdq8GRQJGFGQxpClu/BX8ahpaYTEp+q1MRskjGqtshRBwelSYFBmD0s0hA3h0WU7ce5F6lciFXdEsA6qJjp5xp9Oa/PuMjzX3L4w794wlyVft64dXjcDk8jyYjUrg+/v3rZoMsq6G80nfYj395tsGmKnv86hJn/rSC+6qa684U/ZVZHJ7BTRVhWoVMEtytwBOMxli0otMxvnuRC/siqQMqCYEGltc3XrFR6IQxoMyTIGFW18csaHZ6cagDBNMnXrGAgKNDjfKCzIx5ez8buVM9TKcT8kj1affGNRJrC+94K7/aEPNrbZ7NHg1DUYF0DSgyeFGWq7Fd/hEpwD+stYe9V6knn7hInnD0NvCLnubB0XZFjQ73dhX54j5mw9NCJxwuHHkpP/UJmdHELd3vAnT+vzcg9JN3Q+K6KjIlWY8daqd/w1gS7u3I3ARVuDGczifkl8spt8kSYIsnTpUR5ElKJIUt6HurhjUSaqvveCuw9Ch5lZVoUEI3z9SWQbcqgqXR8Bi9H3dH8CSQFR7kXqa7470DcPpeoInHG54NBV1tnb87L2vovbmwx/G/iHqziUxjzW3wRWFMA46RrEjmNNMSu9PgP4FbrKe6kWh+YPPf9KcLEtBB/NoQgRCsfOJc10PrDt1Op7vuTRN4PXPDqPNraIg0xw4Nc+oAFaTgvoWF97acRTXjiqGoki+1zTJ156uz4nOz62zf2cM6iTUn15w12HoUHOriiRDkny/IJKEjmMXNQC+xTv+AB5ZkhW17UGJWDXdk84FNyxGBWmK7DviruH0bxhCBZPQBDyab5QjO+1ULe5w33wIIXCi1R0oh+mfL/YPWfcnjPPSTb7TmnKs3bY4hRvGvelP4CbjqV7JQpIkGDpO6RPi1PGroiMw/WHp700GepaSdOrrcsdpf53u6w9iAIFjXmPZC919xIYjTW0YlGGGydD932xeugkHG1uxv7E1piU+Y41BnYT60wvuOgwdam7VbJRgUuTAClvfL6gvpDsH8IjCjKjNJ+qlHKb/DUOz0wNNCDhcXgjhuwZGRYZHFad9w9A5mE62ufHyloOot7ef9s3H+UOycdLpOTVX3Kk+9bGTbWjvRxjnWo2nesS5aSjNOXWUotUUn19/Bm58KbLvqFyDLEOWfeH6db0D9nYP8jPMqCjNhjFFVsw3Od3wqAKmHuqsx6vEZ6wxqJNQf3rBXYehQ82tSpCQl2FGva0NHg0wG2QYDRLavVq3AI7WfKJeymFW17eipqEFLq8KTfh7E77r6vJqkCUNNQ0tp33D4A+mfXUONDlcyLIYAQF4NQ1uVcCjanCrGto9Gj4/3Ix/e/rTfvWMc63GoBOb/H+W5KQh3azPX/FkWjAYz7ZKHT1URen4syN0/cO1vl4rAkO8/qFiudN9O9tS3YhVm2tQ0+CARxVxP0c51vKsJhgVCW5Vg0Xu3qOOV4nPWNPnbzGdVn96wV2HoXuaW5UlCSaDAZKmIs2ooMnp7jGAozGfmOhV034n29xwuLzQBDqGBn1tkQBIMuDVfL3sk23d3zAIIXDS6Qks4PrsYBNOtnnQ3OaFR9MC83FdhVOZKyfNGOgV+w+M8A9V6zWMe6KnBYO96Utb/aEpBxYgdQrTjiHjwBByp/+O9tzolupGLF67Gw6XF7lW38r7eJ+jHGujSrJQXpCBqtoWFGXJQdcvniU+Yy25fsMJQP97wV311Cs+pzgT/3nhEGSaTREfNRiNn8kvnvtn7W0eaBogy91fNH29GAFVA/YctaGp1X1qAVfHnHGbRw3xrOFtd8pJC+4Zdw7mjCQL457oacFgbzq31be+QIZX1XCgsRUrPvgaS/7tXFxUPiioN9v5zV0iaZrAqs01cLi8KMqyBNpkkRUUZcmos7uwanMNLho2KGErmaNBliXMnVKOxWt3o87uQo7VCLMS/xKfsZYav/0DTDR6wV0lepWtXvbPZluMkCRA1QBIGiA6VqcieAXqK38/1KfnVzrmuo0GGR5VQ3F2Gu67ZgTKcq3IsKT2r6MeFgwaZN8bWJMiQ5E73uLKvhET/6Ipg+xr2dI/7YHLq6E0J+1U+BoVpJsNqLO78Nv/+xeuGlmoyxDYc8yOmgYHcq2mkG8443WOcjxMHp6PZTdWBIb4bR0jH/Es8Rlrqf3KkMKi0QvuKtGLfuK5f1YIgeY2T3AFrpNt2N/YCn+9D68KhNsb7izLYgj0hBVZwrYDTfCqGrLTTLAY5cCbjyyLCXddUY6Rxck9LBeueCwYVPzVzwwyjP7FVB0BbOwI53DsPmJL6qAbKIus/CYPz8dFwwZhzzE7mpzuuJf4jDUGdRJLdC84FqL5MwkhYGvzBK2i7ryqutUdapg6PJkdYezfzhSYO85NQ6bFGHTfzvOcrR7vgC3eEa0Fg0ZFhlGRYVAkGGUZiuLrBRtk36Ed0ZDsQZfoRVaaJuIemrIs6fJNUzQwqJNconvBsRDJzySEgL3NiyPNzpD1qVtdfQ9jCb4FZf4VuAJAuknBD68ajouHDw77eVLxDVUk/KumD59sAwBfeITY8+pfMJhnNcNsVILC16j4thsZlfjMASc66PorkYusUn2leSIwqEn3/GF8NNAr9pfF9IWxw+Xt83NnmA2BqludF3A1tbqwbletb7VvxxB8f1Ymp+IbqnAErZpWfSvmW9o9KM5OQ4bF0LEM0rdgsLXVi3NLsnDVyIKED1km+2riRC2yGggrzRNBEqKnTSOpyW63Izs7GzabDVlZ/f8lO+FwwdbmiULLyNbm6baK2j9c3Z8wTjcrGJJjPRXInVZVZ6cZe3xcMu311RujIuOLI8147C9fwek+9aJta/eg1tYOACjOTkNOmjEoPPT0Qn4qdNSQQXfbpcNQlmfV9XxoUO+2Y5FVf3q3pxvS1jSB2S9uQ1WtPWilOeB7c1Nnd2FkcSZenjNBl9dKzxjU/cSgjoy9zRMYlvYHsv/Uppb2/odxSY6loxymrwLXkBwrstIMutgyk6okSYLZIMNiVGAxyjAbFEhAjy/aLe2+fwOyJCHLYtT10GiooBuU4RvuPuFwJ8XQbn/mizs/9nCTExv+WYv9x1tD/ty7j9hwx+8+Q7rZAIux+3RBm0eF0+XFr28Zn7JzybHCoW+KupZ2z6l54k7zxsea22DvTxiblKDecOfTm7LTjAzjOFBkybeiumNltUmRYTbI3a796VZNZ1qMOCNPgq3Ng7uuGI4LzszVbY+062riw01OrPm4Bq1uNWmGdvu6yKrzm5RWtwqHywtZAgoyzSjINHf7uT2aSOoFeHrGoKY+cbT3sIDrZP/C2GpSuq2iLmUYx51B7ghig28Bl3+ldbjbm3pbNW0xKLBLXgwdnJ40vStNCLy5/Qha3WpKFxEBgueac6xG36ihENAAHG9xw2RQkGE2BP3c911zdlIvwNMzBjX1yOHydjq1qdO5xv0M4zSj0m2+2H96Uw7DOO4Msgyz0dczNhsUmAzhB3JPkn3VtF/nXqXTraKl3QOTQUGrWw2qFpcMe6vD1bWqWbvHV5veoMiQAHg0geMt7Ug3pQf93ACSegGenjGoBziHyxt0jvHRTn8292Pu3R/GnQ+J8A9Z51oZxvHmP9bQP2zt7yWbFDkmvb/eV027MSTXisZWF3YfsSVk6Lu3uduuK5iNiowWlxdur4qjJ9tQmhtc2jVVhna7VjXzdtSp91Vwk2CQfQfUtHs0pJmUwM/d3OYZEOU8E4FBPQC0urynjlCMYhhbjLJvAVeupaN33LGAK9fKME4gSfIFstkQ3EuOp9NtDzre0g6XV8Phplb85I0vErIYq7e9vqFqZfuOkQUkWYKmCRxvcSHdrASqrCXLKEFvuk5bGGQ5cG61//Qu0XEaHKAE/dwVQ7JTvpxnIjCoU4TT7T0VwF22OJ109i+MO/eGOw9X56V3XyhE8WdU/EPXSiCc9fD3EqoGs6YJuLwaTIqMvHRzQhZjhbPXN9Ni7LYYztIxPdDm8Z1Q5/KqaHf7epWpNLTbddrCYvL922r3qJCUU0fpGmQ55M+d6uU8E4FBnUROhXE7jjY7T5XGPNnPMDbIKAmxx3gIw1iXjB0rrS0mBWlGBcYolc2Mhc4v2iccLqzY+DUON7WiODstIYuxwj1V6v9dcla3xXCSJGFwpgVHT7b5znoXgFtVAQ9Samg31LTF4Ewzjp5sg6fj3HSLUYGAb290qJ87lct5JgKDWmfa3Gq3utT+hVxNrX2f+zIb5EAAd65PXZqbhkEMY90yyLKvJ2f09ZZjNaccS/4X7d1HbGiwtyMv3Zywgy7CPVWqudUTcjGcv5Jdna0dbq+KlnYv0owipYZ2Q01bWI0KBmea0dDS7jurXZHR5lZT6ufWMwZ1ArR5VBzrOl/c8d8nohDGJSG2N+VnMIyTgUGWYTHJSDMqsOi8txwpPRx0EW4bcq3GHhfDpZsUWE0Kzi7KxI+u+gYGZZhTbmi3p6MjJ541CNeeV6T7imyphkEdI/4w7lzs40gUwthkkFGSbem2onpIrhWDMkwscZlkZElCmknxfaRYMHelhy1b4bZhUIb5tCuYMy0G/GTa2Sndk+Rcs34wqPuhza3i6/oWfFXf4usZd6pPfcLR9zA2KpKvN9zpkAj/5/mZZoZxEutcSCSto+TmQBnp0MNBF5G0QZaluKxg9no1/PmLWhxtdqI0x4rK84thiPMq/Z5wrlkfWOu7j/5v/wn853P/1+fHGxUJJdndF2+V5qZhMMM4JYSqgd3fQiLJrreDLuK76ju8NsTybOU1H9dg5aYatLR5oAGQAWSmGTHv8nLcfll5VL4HJT8GdR8dbnLi0sc/Ou19jIqE4uzghVv+UB6cYR7wL9qpRq/bpPQm2ic6JWsb1nxcg59t2AtVEzAoEmQJ0ATgVQUUWcKCa89mWBMABnWfn0fVBEY+uAECIhDGpbkWlOZYA/PGgzMZxqlKkSVYjEqgoIjZkHyrsRMplr3UZGiD16th/LIPYHN6YDJIkKVTQ92a0OD2CmRbjfhs8VTdDINT4nCOuo8UWcLHP7kCsoR+nZVMyUGRfYu+LEYFlgRU+ko1epj7TGQb/vxFLVraPB096eB/S7Ikw6BoaGnz4M9f1OLGC0oT0kbSDwZ1PxRlW3DC4Up0MyhGLEbfNpw0kwKzofsKYaK+OtrshAbA0EMHXpYAteN+RAxqok7MRgUZJgPSzQoMKbxVihKrNMcKGb456VCj7Zrw1dQuzbHGu2mkQ3wlogHPYlQwKN2MsjwrSnPSkG01DqiQ1jSB3Uds2LzvOHYfsUHTBtSylYSoPL8YmWlGeFUBTWhBX9OEBq8qkJlmROX5xQlqIekJe9Q04PhXZ1uMCqzGgd1z7u0UKYoNg0HGvMvL8bMNe+H2ChgUrduq73mXl3MhGQHgqu9+P98Jhwu2fhwVSbHnr/5lNSmwmgxcid+hp1OkTsZxT/NA13kftYBvuJv7qKkrBnU/Maj1x19oxGyQA6U5uZ85mKYJzH5xG6pq7UGnSAG+Cl11dhdGFmfi5TkTIHecv5zo7VSpSs+VyeiURP4OcOibkl6g0IiidBQcYaGR3oR7itSeY3a0tHs4PB5DBoPMLVg6l+gpIgY1JQ1/T9lfK9ukJOexj3oQ7ilSn1Qfx+v/ONxteLyqtgWL1+7m8DilvJ6miOL5O8DxFdI1gywjw2JAQZYFZ+ZZUZKThvwMM7IsRliMCkO6jzqfIhWK/xSp9/bUw+HyoijLErjeFqOCoiwzHC4VqzbXcJU4pSxNE1i1uSbhvwO6COqVK1di6NChsFgsmDhxIrZt2xbW41577TVIkoTp06fHtoEUN/5gzs/0bZc6Y5AVBZkWZJgNDOUo8p8iddLpQddlKv5TpAqyLKi3tYU1PE6UiiKZIoqlhAf166+/jvnz52Pp0qXYsWMHRo8ejWnTpqGhoeG0jzt48CDuu+8+XHrppXFqKcWCySAjO82IgiwLzugUzFkWY0qfzZxosixh7pRyZJgV1NldaPOo0DSBNo+KOrsLGWYF00YVwavhtMPjHk2gydn3I12J9CycKaJ4/A4k/JXwySefxO233445c+bg3HPPxerVq2G1WvHCCy/0+BhVVfHd734XDz30EIYNGxbH1lJ/GRVfMBdlWzB0UDqG5FoxKMOMDLNhQO9nToTJw/Ox7MYKjCzOhNPlRYPDBafLi5HFmVh2YwUuGZ4f1vB4ntUU55YTxUe4U0Sx/h1I6GIyt9uN7du3Y9GiRYHbZFnG1KlTsXXr1h4f9/DDD6OgoADf+9738Le//e2038PlcsHlOlWP227nMF28mQwy0k0GWM2sma03k4fn46Jhg0JuO9E0gfKCDFTVtqAoS+62havZ6cHI4kyMKun/NkciPfJPESX6dyChXZjGxkaoqorCwsKg2wsLC1FXVxfyMZ988gl+85vfYM2aNWF9j+XLlyM7OzvwUVZW1u920+nJkoR0s2+e+Yw8K4bkWpGbbmJI65T/FKkpIwajYkh2YC1AOMPjc6eUc+0ApSy9/A4k1VhjS0sLbrnlFqxZswb5+eEth1+0aBFsNlvg4/DhwzFu5cBlNXWszh5kRWGWb56Zw9nJrbfhcW7NomTXW617PfwOJHToOz8/H4qioL6+Puj2+vp6FBUVdbt/TU0NDh48iMrKysBtmuabOzAYDNi7dy/Ky4PL7pnNZpjN5hi0fmCTJAlGRYLZ4CsyMtBrZqey0w2PEyWzcAuZJPp3IOElRCdOnIgJEybg6aefBuAL3jPOOAN33XUXFi5cGHTf9vZ2VFdXB932wAMPoKWlBb/85S8xYsQImEynn9RnCdG+MxlkpBl99bItRlb/IqLklUy17hNemWz+/PmYPXs2xo8fjwkTJmDFihVobW3FnDlzAACzZs1CaWkpli9fDovFgvPOOy/o8Tk5OQDQ7XbqP/9hFmkmnjJFRMmnpzrqXQuZ+DsdFllBUZaMOrsLqzbX4KJhg3QxcpTwoJ4xYwaOHz+OJUuWoK6uDmPGjMGGDRsCC8wOHToEWWZAxItRkQOnTLHXTETJqvPJZBp8C7IeemcP5l1ejouG5YddyKRiSHZC2h/UpkQPfccbh76DSZKENKMSOAaSRUaIKNmt+bgGP9uwF6omYFCkbmd9/8e4IdhY1YCCTHPIHrOmCTQ4XHjiO6MxZcTgBPwEwRLeo6b4MypyIJh5BCQRpQL/MZTHW9rxyw+r4dUEzAYJsuTrfMgSIEsa3F6Bd7+oRbrJNydtkbtvG9VbMR8G9QCgyKd6zWmcayaiFNN59XaLywtHuxcSACEkoFM/RJZkGBQNTrcXxTkZaGr1JEUxHwZ1ijIbfQvA0kwKLEYWGiGi1NR19bZX09DSDggAHtU3O610Gt6WJUAFMHpIDv5xsAl1dhdyrEaYFRkuVUNzx6pvPRXzYVCnCEWWAj1mq8kQ9A+TiCgVhVq93eY51TERALyaBlk61WvWhK+TPbk8HzeOLQ30xG2agFGWMLI4s9s+6kRjUCcpWfKdiZpmVGAxySzPSUQDTqhjKHPSjKi1tUPtqDAmhC+wJQCa0OBVBbKtxsBWrWQo5sOgThKdg9lslDmcTX3iX3Cj5xclonCFOoZSkiQMzjCjzt4OwBfSmqZBk6TAqu95l5fDYOhYZNZR617PGNQ6xj3NFE3hlkskioVYvEnsfAxl59XbgzN9ZaMbWtp927I0QJZ8Pel5l5fj9svKe3pKXWJQ6wgrgVGs9FQusaq2BYvX7tZVuURKPbF6k3i6YyjzM3wLy/LSzag8vwhDctMDw93JhgVP+qk/BU/826bMRgUWI+eZKTY0TWD2i9tQVWsPKpcI+Lai1NldGFmciZfnTOAwOEVdrGtqn3p+NeTq7VR4E5p8by2SnCRJyDAbUJRtwRl5VhRkWZCdZmRIU8yEWnDj17VcIlE0dV2VbTEqkGXfepuiLDMcLhWrNtd0O1oyEno4hjLWOPQdB/6tU1aTAdaOf6hE8RJqwU1nZkWGTRNocrrj3DJKdZG8SezPgq5EH0MZawzqGDEqMtLNBlhZcIQSrKcFN356K5dIqSOebxKTYfV2XzGoo0SSJFiMMqxGA9JMCkxJuGCBUtPpFtzosVwipQ6+SYwOpkk/pZkUFGZZcGaeFcXZaci2GhnSpCuyLGHulHJkmBXU2V1o86jQNIE2j4o6u0t35RIpdfjfJJ50etB13bL/TWJ5QQbfJPaCidJPVpMB6WYDX+RI1wbCghvSH75JjA5uzyIaQFiZjBIhaB91R01tFtsJH4OaiIhijm8S+46LyYiIKOZSeVV2rHGOmoiISMcY1ERERDrGoCYiItIxBjUREZGOMaiJiIh0jEFNRESkYwxqIiIiHWNQExER6RiDmoiISMcY1ERERDrGoCYiItIxBjUREZGOMaiJiIh0jEFNRESkYwxqIiIiHWNQExER6RiDmoiISMcY1ERERDrGoCYiItIxBjUREZGOMaiJiIh0jEFNRESkY4ZEN4AoljRNYM8xO5qcbuRZTRhVkgVZlhLdLCKisDGoKWVtqW7Eqs01qGlwwKMKGBUJ5QUZmDulHJOH5ye6eUREYeHQN6WkLdWNWLx2N6pq7Ug3G1CQaUa62YCq2hYsXrsbW6obE91EIqKwMKgp5WiawKrNNXC4vCjKssBiVCDLEixGBUVZZjhcKlZtroGmiUQ3lYioVwxqSjl7jtlR0+BArtUESQqej5YkCTlWI2oaHNhzzJ6gFhIRhY9BTSmnyemGRxUwKaH/eZsVGR5NoMnpjnPLiIgix6CmlJNnNcGoSHCrWsivu1QNRllCntUU55YREUWOQU1JS9MEdh+xYfO+49h9xBaYcx5VkoXyggycdHogRPA8tBACzU4PygsyMKokKxHNJiKKiC6CeuXKlRg6dCgsFgsmTpyIbdu29XjfNWvW4NJLL0Vubi5yc3MxderU096fUtOW6kbMfnEb7vjdZ7jvj5/jjt99htkvbsOW6kbIsoS5U8qRYVZQZ3ehzaNC0wTaPCrq7C5kmBXMnVLO/dRElBQSHtSvv/465s+fj6VLl2LHjh0YPXo0pk2bhoaGhpD337RpE26++WZ89NFH2Lp1K8rKynDNNdfg6NGjcW45JUo4W68mD8/HshsrMLI4E06XFw0OF5wuL0YWZ2LZjRXcR01ESUMSXccG42zixIm48MIL8cwzzwAANE1DWVkZ7r77bixcuLDXx6uqitzcXDzzzDOYNWtWt6+7XC64XK7A53a7HWVlZbDZbMjK4tBnstE0gdkvbkNVrR1FWZagVd1CCNTZXRhZnImX50yALEusTEZESS+hPWq3243t27dj6tSpgdtkWcbUqVOxdevWsJ7D6XTC4/EgLy8v5NeXL1+O7OzswEdZWVlU2k6JEenWK1mWUDEkG1NGDEbFkGyGNBElnYQGdWNjI1RVRWFhYdDthYWFqKurC+s5FixYgJKSkqCw72zRokWw2WyBj8OHD/e73ZQ43HpFRANNUtf6fuyxx/Daa69h06ZNsFgsIe9jNpthNpvj3DKKlc5bryyy0u3r3HpFRKkmoT3q/Px8KIqC+vr6oNvr6+tRVFR02sc+8cQTeOyxx/DXv/4V559/fiybSTrCrVdENNAkNKhNJhPGjRuHjRs3Bm7TNA0bN27EpEmTenzc448/jkceeQQbNmzA+PHj49FU0gluvSKigSbhQ9/z58/H7NmzMX78eEyYMAErVqxAa2sr5syZAwCYNWsWSktLsXz5cgDAz372MyxZsgSvvvoqhg4dGpjLzsjIQEZGRtzazdXEiePfeuU/wtKmCRhlCSOLM3mEJRGlnIQH9YwZM3D8+HEsWbIEdXV1GDNmDDZs2BBYYHbo0CHI8qmO/6pVq+B2u/Ef//EfQc+zdOlS/M///E9c2sxzjhNv8vB8XDRsEN8sEVHKS/g+6niz2+3Izs7u8z5qf7ENh8uLXKsJJkWGW9Vw0ulBhllhMQ0iIoqqhFcmSyY855iIiOKNQR0BnnNMRETxlvA56mQSTrENG4ttJBQX+RFRqmFQR4DFNvSNi/yIKBVx6DsCfSm20dOZyRRd4ZyoFSn+3RGRHrBHHQF/sY3Fa3ejzu5CjtUIsyLDpWpo7lj13bnYBnt48dF1kZ9//YBFVlCUJaPO7sKqzTW4aNigsIfB+XdHRHrBHnWEwj3nOBY9PAot2ov8+HdHRHrCHnUf9FZsIxY9POpZNBf58e+OiPSGQd1H/nOOQ4mkh9fTc1D4ornIL9K/O64yJ6JYY1DHALdxxZd/kV9VbQuKsuSggPUv8htZnBnWiVqR/N1xHpuI4oFz1DHQuYcXCrdxRVc0T9QK9+/ucJOT89hEFBcM6hjgmcnxF+4iv96E83c3bHAGNvyzlqVkiSguOPQdA5Fu46LoiMaJWuH83V17XhGe/aiaaxCIKC4Y1DHCM5MT43SL/MLV29+dRxNcg0BEccOgjiGemZy8Tvd3t/uIjaVkiShuGNQxFo0eHiVGT3930VxlTkTUGy4mI4pQNFeZExH1hkFN1AfRWmVORNQbSXTdg5Li7HY7srOzYbPZkJWV/EOTrIyVWLz+RBRrnKNOYqyMlXhcg0BEscah7yTFE56IiAYGBnUS6nrCEytjERGlLgZ1Eor2+ctERKRfDOokFM4JTx5WxiIiSglcTJaEonn+cqJx1TQR0ekxqJNQqlTG4qp1IqLeceg7CaVCZSyuWiciCg+DOkklc2UsrlonIgofh76TWLKezhXJqvVUKSbCuXgi6isGdZJLxspY4axaT6XznDkXT0T9waFvirvOq9ZDSaZV673hXDwR9ReDmuLOv2r9pNODrmfC+Fetlxdk6H7Vem84F09E0cCgprhLhVXr4WAFOSKKBgY1JUQyr1oPFyvIEVE0cDEZJUyyrloPVypVkCOixGFQU0Il46r1cKVKBTkiSiwOfRPFyECZiyei2GJQE8XQQJiLJ6LYkkTX/TEpzm63Izs7GzabDVlZHHKk+GBlMiLqK85RE8VBKs/FE1FsceibiIhIxxjUREREOsagJiIi0jEGNRERkY4xqImIiHSMQU1ERKRjDGoiIiId00VQr1y5EkOHDoXFYsHEiROxbdu2097/jTfewDnnnAOLxYKKigqsX78+Ti0lIiKKr4QH9euvv4758+dj6dKl2LFjB0aPHo1p06ahoaEh5P23bNmCm2++Gd/73vewc+dOTJ8+HdOnT8c///nPOLeciIgo9hJeQnTixIm48MIL8cwzzwAANE1DWVkZ7r77bixcuLDb/WfMmIHW1la88847gdsuuugijBkzBqtXr+71+7GEKBERJZOE9qjdbje2b9+OqVOnBm6TZRlTp07F1q1bQz5m69atQfcHgGnTpvV4f5fLBbvdHvRBRESULBIa1I2NjVBVFYWFhUG3FxYWoq6uLuRj6urqIrr/8uXLkZ2dHfgoKyuLTuOJiIjiIOUP5Vi0aBHmz58f+Nxms+GMM85gz5qIiBIuMzMTknT6k/QSGtT5+flQFAX19fVBt9fX16OoqCjkY4qKiiK6v9lshtlsDnzuD2j2rImIKNHCWS+V0KA2mUwYN24cNm7ciOnTpwPwLSbbuHEj7rrrrpCPmTRpEjZu3Igf/ehHgdvef/99TJo0KazvWVJSgsOHD4f1Loa6s9vtKCsrw+HDh7kYrw94/fqH169/eP36JxbXLzMzs9f7JHzoe/78+Zg9ezbGjx+PCRMmYMWKFWhtbcWcOXMAALNmzUJpaSmWL18OALjnnnswZcoU/OIXv8A3v/lNvPbaa/jss8/w3HPPhfX9ZFnGkCFDYvbzDBRZWVn8Re8HXr/+4fXrH16//on39Ut4UM+YMQPHjx/HkiVLUFdXhzFjxmDDhg2BBWOHDh2CLJ9a8zZ58mS8+uqreOCBB7B48WJ84xvfwLp163Deeecl6kcgIiKKmYTvo6bkwn3o/cPr1z+8fv3D69c/ibp+Ca9MRsnFbDZj6dKlQQv0KHy8fv3D69c/vH79k6jrxx41ERGRjrFHTUREpGMMaiIiIh1jUBMREekYg5qIiEjHGNTUzcqVKzF06FBYLBZMnDgR27Zt6/G+a9aswaWXXorc3Fzk5uZi6tSpp73/QBDJ9evstddegyRJgSp9A1Wk16+5uRnz5s1DcXExzGYzRowYgfXr18eptfoT6fVbsWIFzj77bKSlpaGsrAz33nsv2tvb49Raffn4449RWVmJkpISSJKEdevW9fqYTZs24YILLoDZbMbw4cPx0ksvRb9hgqiT1157TZhMJvHCCy+IPXv2iNtvv13k5OSI+vr6kPefOXOmWLlypdi5c6eoqqoSt956q8jOzhZHjhyJc8v1IdLr53fgwAFRWloqLr30UvGtb30rPo3VoUivn8vlEuPHjxfXX3+9+OSTT8SBAwfEpk2bxK5du+Lccn2I9Pr9/ve/F2azWfz+978XBw4cEO+9954oLi4W9957b5xbrg/r168X999/v3j77bcFALF27drT3n///v3CarWK+fPniy+//FI8/fTTQlEUsWHDhqi2i0FNQSZMmCDmzZsX+FxVVVFSUiKWL18e1uO9Xq/IzMwUL7/8cqyaqGt9uX5er1dMnjxZPP/882L27NkDOqgjvX6rVq0Sw4YNE263O15N1LVIr9+8efPElVdeGXTb/PnzxcUXXxzTdiaDcIL6Jz/5iRg1alTQbTNmzBDTpk2Lals49E0Bbrcb27dvx9SpUwO3ybKMqVOnYuvWrWE9h9PphMfjQV5eXqyaqVt9vX4PP/wwCgoK8L3vfS8ezdStvly/P/3pT5g0aRLmzZuHwsJCnHfeeVi2bBlUVY1Xs3WjL9dv8uTJ2L59e2B4fP/+/Vi/fj2uv/76uLQ52W3dujXoegPAtGnTwn69DFfCa32TfjQ2NkJV1UCddb/CwkJ89dVXYT3HggULUFJS0u0f70DQl+v3ySef4De/+Q127doVhxbqW1+u3/79+/Hhhx/iu9/9LtavX4/q6mrceeed8Hg8WLp0aTyarRt9uX4zZ85EY2MjLrnkEggh4PV68YMf/ACLFy+OR5OTXl1dXcjrbbfb0dbWhrS0tKh8H/aoKWoee+wxvPbaa1i7di0sFkuim6N7LS0tuOWWW7BmzRrk5+cnujlJSdM0FBQU4LnnnsO4ceMwY8YM3H///Vi9enWim5YUNm3ahGXLluHZZ5/Fjh078Pbbb+Pdd9/FI488kuimUSfsUVNAfn4+FEVBfX190O319fUoKio67WOfeOIJPPbYY/jggw9w/vnnx7KZuhXp9aupqcHBgwdRWVkZuE3TNACAwWDA3r17UV5eHttG60hf/v0VFxfDaDRCUZTAbSNHjkRdXR3cbjdMJlNM26wnfbl+Dz74IG655RbcdtttAICKigq0trbi+9//Pu6///6gkwupu6KiopDXOysrK2q9aYA9aurEZDJh3Lhx2LhxY+A2TdOwceNGTJo0qcfHPf7443jkkUewYcMGjB8/Ph5N1aVIr98555yD3bt3Y9euXYGPG264AVdccQV27dqFsrKyeDY/4fry7+/iiy9GdXV14A0OAOzbtw/FxcUDKqSBvl0/p9PZLYz9b3oEj4Ho1aRJk4KuNwC8//77p3297JOoLk2jpPfaa68Js9ksXnrpJfHll1+K73//+yInJ0fU1dUJIYS45ZZbxMKFCwP3f+yxx4TJZBJvvvmmqK2tDXy0tLQk6kdIqEivX1cDfdV3pNfv0KFDIjMzU9x1111i79694p133hEFBQXipz/9aaJ+hISK9PotXbpUZGZmij/84Q9i//794q9//asoLy8XN910U6J+hIRqaWkRO3fuFDt37hQAxJNPPil27twp/vWvfwkhhFi4cKG45ZZbAvf3b8/68Y9/LKqqqsTKlSu5PYvi4+mnnxZnnHGGMJlMYsKECeL//u//Al+bMmWKmD17duDzM888UwDo9rF06dL4N1wnIrl+XQ30oBYi8uu3ZcsWMXHiRGE2m8WwYcPEo48+Krxeb5xbrR+RXD+PxyP+53/+R5SXlwuLxSLKysrEnXfeKU6ePBn/huvARx99FPL1zH/NZs+eLaZMmdLtMWPGjBEmk0kMGzZMvPjii1FvF4+5JCIi0jHOURMREekYg5qIiEjHGNREREQ6xqAmIiLSMQY1ERGRjjGoiYiIdIxBTUREpGMMaiIiIh1jUBPpgCRJWLduXdy/79ChQ7FixYq4f99Eu/XWWzF9+vREN4MoLAxqojg4fvw45s6dizPOOANmsxlFRUWYNm0aPv30UwBAbW0trrvuugS38vQ+//xz3HDDDSgoKIDFYsHQoUMxY8YMNDQ0APAdmShJEpqbmxPb0E4OHjwISZJ43jclNR5zSRQH3/72t+F2u/Hyyy9j2LBhqK+vx8aNG3HixAkA6PUY0UQ7fvw4rrrqKvzbv/0b3nvvPeTk5ODgwYP405/+hNbW1oiea6AdP0nUb1GvHk5EQU6ePCkAiE2bNvV4HwBi7dq1gc8//fRTMXr0aGE2m8W4cePE2rVrBQCxc+dOIcSpwwM++OADMW7cOJGWliYmTZokvvrqq8BzVFdXixtuuEEUFBSI9PR0MX78ePH+++8Hfd8zzzxTPPXUU73+DGvXrhUGg0F4PJ6QXz9w4ECPBxlMmTJFzJs3T9xzzz1i0KBB4vLLLxdCCLF7925x7bXXivT0dFFQUCD+67/+Sxw/fjzwnFOmTBF33323+PGPfyxyc3NFYWFht8NeqqqqxMUXXyzMZrMYOXKkeP/994OuZdc2+Q9U8B9+8vOf/1wUFRWJvLw8ceeddwq3293rtSCKNw59E8VYRkYGMjIysG7dOrhcrl7vb7fbUVlZiYqKCuzYsQOPPPIIFixYEPK+999/P37xi1/gs88+g8FgwP/7f/8v8DWHw4Hrr78eGzduxM6dO3HttdeisrIShw4divhnKCoqgtfrxdq1a0OeU1xWVoa33noLALB3717U1tbil7/8ZeDrL7/8MkwmEz799FOsXr0azc3NuPLKKzF27Fh89tln2LBhA+rr63HTTTcFPe/LL7+M9PR0/P3vf8fjjz+Ohx9+GO+//z4AQFVVTJ8+HVarFX//+9/x3HPP4f777w96/LZt2wAAH3zwAWpra/H2228HvvbRRx+hpqYGH330EV5++WW89NJLeOmllyK+NkQxl+h3CkQDwZtvvilyc3OFxWIRkydPFosWLRKff/554Ovo1AtctWqVGDRokGhrawt8fc2aNT32qP3effddASDocV2NGjVKPP3004HPw+1RCyHE4sWLhcFgEHl5eeLaa68Vjz/+eOCc485t6npE4pQpU8TYsWODbnvkkUfENddcE3Tb4cOHBQCxd+/ewOMuueSSoPtceOGFYsGCBUIIIf7yl78Ig8EgamtrA1/v2qP29/T9181v9uzZ4swzzww6DvM73/mOmDFjRljXgiie2KMmioNvf/vbOHbsGP70pz/h2muvxaZNm3DBBReE7MHt3bsX559/PiwWS+C2CRMmhHze888/P/DfxcXFABBY3OVwOHDfffdh5MiRyMnJQUZGBqqqqvrUowaARx99FHV1dVi9ejVGjRqF1atX45xzzsHu3bt7fey4ceOCPv/888/x0UcfBUYbMjIycM455wAAampqQv58/p/R//Pt3bsXZWVlQfP7PV2nUEaNGgVFUUI+N5GeMKiJ4sRiseDqq6/Ggw8+iC1btuDWW2/F0qVL+/WcRqMx8N+SJAEANE0DANx3331Yu3Ytli1bhr/97W/YtWsXKioq4Ha7+/z9Bg0ahO985zt44oknUFVVhZKSEjzxxBO9Pi49PT3oc4fDgcrKSuzatSvo4+uvv8Zll10W8ufz/4z+n6+/YvncRNHEVd9ECXLuueeG3Dt99tln45VXXoHL5YLZbAYA/OMf/4j4+T/99FPceuutuPHGGwH4wvHgwYP9aXIQk8mE8vLywKpv/0puVVV7fewFF1yAt956C0OHDoXB0LeXobPPPhuHDx9GfX09CgsLAXS/TpG0iUiv2KMmirETJ07gyiuvxCuvvIIvvvgCBw4cwBtvvIHHH38c3/rWt7rdf+bMmdA0Dd///vdRVVWF9957L9Br9feaw/GNb3wDb7/9Nnbt2oXPP/888Lx98c477+C//uu/8M4772Dfvn3Yu3cvnnjiCaxfvz7wM5x55pmQJAnvvPMOjh8/DofD0ePzzZs3D01NTbj55pvxj3/8AzU1NXjvvfcwZ86csEP16quvRnl5OWbPno0vvvgCn376KR544AEAp65TQUEB0tLSAovVbDZbn35+okRiUBPFWEZGBiZOnIinnnoKl112Gc477zw8+OCDuP322/HMM890u39WVhb+/Oc/Y9euXRgzZgzuv/9+LFmyBACC5q178+STTyI3NxeTJ09GZWUlpk2bhgsuuKBPP8O5554Lq9WK//7v/8aYMWNw0UUX4Y9//COef/553HLLLQCA0tJSPPTQQ1i4cCEKCwtx11139fh8JSUl+PTTT6GqKq655hpUVFTgRz/6EXJyciDL4b0sKYqCdevWweFw4MILL8Rtt90WWPXtv04GgwG/+tWv8Otf/xolJSUh3xgR6Z0kRIi9FkSkK7///e8xZ84c2Gw2pKWlJbo5uvXpp5/ikksuQXV1NcrLyxPdHKKo4Bw1kQ799re/xbBhw1BaWorPP/8cCxYswE033cSQ7mLt2rXIyMjAN77xDVRXV+Oee+7BxRdfzJCmlMKgJtKhuro6LFmyBHV1dSguLsZ3vvMdPProozH7fr///e9xxx13hPzamWeeiT179sTse/dHS0sLFixYgEOHDiE/Px9Tp07FL37xi0Q3iyiqOPRNRGhpaUF9fX3IrxmNRpx55plxbhER+TGoiYiIdIyrvomIiHSMQU1ERKRjDGoiIiIdY1ATERHpGIOaiIhIxxjUREREOsagJiIi0rH/DzXr22wKfeHYAAAAAElFTkSuQmCC"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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IhMjEFNRERkYgxqIiIiE2NQExERmRiDmoiIyMQY1ERERCbGoCYiIjIxBjUREZGJMaiJiIhMLKbKZD/72c9i/oT/+Z//OeDGEBERUaSYan2PHDky4v2jR4/C5/OhuLgYAHDy5Ek4nU6Ul5dj//79SWloorDWNxERZZKYhr4PHDgQfvvhD3+I888/H3v37sXx48dx/Phx7N27F5/97GfxwAMPJLu9REREOSXu07Nqa2vx4osvYuLEiRG379y5E1//+tdx4MCBhDYw0dijplzCU62IMl/cp2c1NjZC07Q+t+u6jubm5oQ0iogGb1t9K9ZubUBDixcBXcCqSKgtL8DCGbU8J5oog8S96vuyyy7Dt7/9bezatSt8286dO7Fw4ULMnDkzoY0jooHZVt+KZRvrsLfRg3y7BeUuO/LtFuxtbMOyjXXYVt+a7iYSUYziDuqnnnoKlZWVmDx5Mux2O+x2O6ZMmYKKigo8+eSTyWgjEcXBMATWbm2AV9VQWeiAw6pAliU4rAoqC+3wqjrWbm2AYcQ160VEaRL30PfQoUPx6quvYt++ffjwww8BAGeffTbGjBmT8MYRUfz2HPGgocWLEqcNkhQ5Hy1JEoqdVjS0eLHniAfjhxelqZVEFKu4gzpkxIgREEKgtrYWFsuAPw0RJdhxnx8BXcCmRB8wsysy3IbAcZ8/xS0jooGIe+jb5/PhxhtvhNPpxLhx43Dw4EEAwKJFi/Dggw8mvIFEFJ9Spw1WRYJfN6J+XNUNWGUJpU5biltGA2EYAnWH3di67yjqDrvjnrIY7P0p/eLuCi9duhT/+Mc/sGXLFlx++eXh22fOnIl7770XS5YsSWgDiSg+46oLUVtegL2NbagslCOGv4UQOOkLYGyVC+OquT3R7Aa7cp8r/7ND3D3ql19+GY899hguuuiiiCeAcePGoaGhYUCNWLNmDUaMGAGHw4GpU6dix44dp7x+9erVOOuss5CXl4eamhrccccd6OzsHNDXJso2sixh4YxaFNgVNHlUdAR0GIZAR0BHk0dFgV3Bwhm13E9tcoNduc+V/9kj7qA+evQoysvL+9ze3t7eZ+FKLJ5//nksXrwYK1aswK5duzBhwgTMmjULLS0tUa9/7rnnsGTJEqxYsQJ79+7FL3/5Szz//PNYtmxZ3F+bKFtNH12GlVePx9gqF3yqhhavCp+qYWyVCyuvHs/elMkNduU+V/5nl7iHvidPnoxXXnkFixYtAoBwOD/55JOYNm1a3A149NFHcfPNN2PBggUAgHXr1uGVV17BU089FXUYfdu2bfjc5z6HuXPnAgguavvmN7+J//u//4v7axNls+mjy3DhqCGsTGYC8VaIG+zKfa78zy5xB/XKlStxxRVX4IMPPoCmafjpT3+KDz74ANu2bcPWrVvj+lx+vx87d+7E0qVLw7fJsoyZM2di+/btUe8zffp0/OY3v8GOHTswZcoU7N+/H6+++iquv/76qNerqgpVVcPvezyeuNpIlMlkWeITcZoNZJ54sCv3ufI/u8Q99H3RRRdh9+7d0DQN48ePx+uvv47y8nJs374dkyZNiutztba2Qtd1VFRURNxeUVGBpqamqPeZO3cu7r//flx00UWwWq2ora3FJZdc0u/Q96pVq1BUVBR+q6mpiauNREQDNdB54sGu3OfK/+wSd1ADwYM51q9fjx07duCDDz7Ab37zG4wfPz7RbYtqy5YtWLlyJR5//HHs2rULL730El555ZV+T+5aunQp3G53+O3QoUMpaScR5bbBzBOHVu6f8AXQ+9yk0Mr92vKCflfuD/b+ZC5xB7WiKFEXeh07dgyKosT1ucrKyqAoSp/DPJqbm1FZWRn1Pvfccw+uv/563HTTTRg/fjyuvvpqrFy5EqtWrYJh9H31aLfbUVhYGPFGRJRs8cwT9zbYlftc+Z9d4g7q/k7FVFUVNlt8wyg2mw2TJk3C5s2bw7cZhoHNmzf3uzDN5/NBliObHXqBEOeJnURESRPLPHHgFPPEg125z5X/2SPmxWQ/+9nPAARfCT755JMoKCgIf0zXdbz11ls4++yz427A4sWLMX/+fEyePBlTpkzB6tWr0d7eHl4FPm/ePAwbNgyrVq0CAMyePRuPPvooJk6ciKlTp6K+vh733HMPZs+eHXePnogoWXrOEzvkvs9NscwTD3blPlf+Z4eYg/onP/kJgGCvdd26dRGhaLPZMGLECKxbty7uBlx77bU4evQoli9fjqamJpx//vnYtGlTeIHZwYMHI3rQd999NyRJwt13341PP/0UQ4cOxezZs/HDH/4w7q9NRJQsiaoQN9iV+1z5n/kkEed48aWXXoqXXnoJJSUlyWpTUnk8HhQVFcHtdnO+mrKKphn43/cb8elJH4YVOzH7vCpYLANaL0oJElr17VV1FDutsCsyVN3ASV8ABXaFQ9AUk7iDOtMxqCkbrX+rAWu2NKCtIwADwcUnrjwrbrukFjd/vjbdzctpEfuoDQGrzHrbFJ+4g/prX/sapkyZgrvuuivi9oceegh///vf8cILLyS0gYnGoKZss/6tBvxo00fQDQGLIkGWAEMAmi6gyBLuuvwshnWaxVuZjKinuIN66NChePPNN/vsm66rq8PMmTP7bLUyGwY1ZRNNMzB55V/g9gVgs0iQpe6hbkMY8GsCRU4r3l02k8PgRBkq7r9cr9cbdRuW1WpleU6iFPvf9xvR1hHo6klH/jnLkgyLIqGtI4D/fb8xTS0kosGKO6jHjx+P559/vs/tGzZswDnnnJOQRhFRbD496QvOSfcziipLgOi6jogyU9yHctxzzz346le/ioaGBnzhC18AAGzevBm/+93vTD8/TZRthhU7ISM4Jx0trA0BSF3XEVFmirtHPXv2bLz88suor6/Hrbfeiv/6r//C4cOH8Ze//AVz5sxJQhOJqD+zz6uCK88KTRcwRGQJXUMY0HQBV54Vs8+rSlMLiWiwuD2LKMmSveKXq76JslvcQ99EZmemrTADOYs4XqEQDu2j1hEc7i5ych81UTaIqUddWlqKffv2oaysDCUlJX1Ogunp+PHjCW1gorFHnd1SEYzxtCVYlUpDidMGmyLDrxs4kaSqVKxMRpSdYupR/+QnP4HL5QIArF69OpntIRqw/oJxb2Mblm2sS2m5xt5nEYde3DpkBZWFMpo8KtZubcCFo4YkrLdvsci4+rPDEvK5iMg8OEdNWcEwBOY/vQN7Gz0RwQgED0Bo8qgYW+XCswumpGQYvO6wG9/+9bvIt1vgsPY9OakjoMOnavjF9ZNz/sAEM01VEJlRTD3qeAqZMPwoHfYc8aChxYsSp63P1IwkSSh2WtHQ4sWeI56UBGMsZxG7T3EWca4w01QFkVnFFNTFxcWnnJfuSdf1QTWIaCB6BqOAQKffgGYYsMgyHDY55cGYiLOIs52ZpiqIzCymoP7rX/8a/v8nn3yCJUuW4IYbbsC0adMAANu3b8ezzz6LVatWJaeVRKcRCsaTHQG4OwJQNR1CAJIE2C0KivKsKQ3GRJ1FnK3SMYdPlKliCuoZM2aE/3///ffj0UcfxTe/+c3wbV/+8pcxfvx4PPHEE5g/f37iW0lJl+nzhOOqCzGkwIY9RzyQAFgUGZIMCAF0+DX4/BrGVRemLBhlWcLCGbVYtrEOTR416lnEC2fUZtRjnEhmm6ogMrO491Fv374d69at63P75MmTcdNNNyWkUZRaWTdPGHreFz3eT8OSyemjy7Dy6vHhx9bddRbx2CpX5j62CcI5fDI7IQRUzYBfN+DXDAR0AwFN4IwhqS/HG3dQ19TUYP369XjooYcibn/yySdRU1OTsIZRamTLPOGeIx4c8/pRVeToGvo2wkPfeVYFhXlWHPP6U95Dmz66DBeOGpLRoxXJwDl8MhPdEPBrwUBWdb0rmAV6b4qKda1WosUd1D/5yU/wta99DX/+858xdepUAMCOHTvw8ccf4w9/+EPCG0jJk03zhKEeWrnLjhKnDZ2BHovJrDKEAFq8alp6aLIscfi2F87hU7pouhHsKffqLZtZ3GWLrrzySuzbtw+zZ8/G8ePHcfz4ccyePRv79u3DlVdemYw2UpLEM09odj17aJIkIc+mwOWwIs+mQJIk9tBMJjSHX2BX0ORR0RHQYRgCHQEdTR415+fwafA03UCHX4e7I4BWr4ojJzvwSWs7Dh73odnTiRM+P9pVzfQhDQyw1ndNTQ1WrlyZ6LZQimXTPCF7aJmHc/g0WJpuQDNEcP5YF9D0YC852rB1JhtQUP/tb3/DL37xC+zfvx8vvPAChg0bhl//+tcYOXIkLrrookS3kZIk0+YJT7UynausMxPn8CkaIQR0Q0Azuv/VdKPPbdkUxqcSd1D/4Q9/wPXXX4/rrrsOu3btgqqqAAC3242VK1fi1VdfTXgjKTkyqRfa38r0b39+FIrybOEn+R/MORe/eGs/e2gZhHP4uUWIUPAKaEbf8NW7bqducdf6njhxIu644w7MmzcPLpcL//jHPzBq1Ci89957uOKKK9DU1JSstiYEa31H6l71rUfthZph1Xd/K9ObPSr8uo58mwWyJIXD+1sXjUJru5+nSBGliWGIriFoA5ouEDCCw9GZHsKSJGFkWX7Kv27cPeqPPvoIn//85/vcXlRUhJMnTyaiTZRCZp8n7G9luhYQ6AxoCOgCEnSMLHMioAu8f/gkbv7Nu8i3KZAlGVZFwkvvHTbF90KUbQJdYRxaQa3pwfli3ciNIelUiTuoKysrUV9fjxEjRkTc/vbbb2PUqFGJahelkJnnCaOtTBdC4GhbJ3QBWBUJmmHArwnoQsCn6tAMARkSRgxxIGCIjNsTng6ZXpmOkivUQ+69rSlX5ojTLe6gvvnmm/Gd73wHTz31FCRJwpEjR7B9+3bceeeduOeee5LRRkoBs84TRluZ3hkIPmFYZAmShPBcV6vXDwHAapEQMAz4dYE8W+btCU+1rKtMR4MS7iFn0D7jbBd3UC9ZsgSGYeCyyy6Dz+fD5z//edjtdtx5551YtGhRMtpIOSzaynTN6K46FvpXMwRUTYciS5AAaCI0F6awdvQpZEtlOoqfECIcxD1DmcPW5hNXUOu6jnfeeQe33XYb/vu//xv19fXwer0455xzUFBQkKw2Ug6LtjLdIsuQJMCAgGEADqsCiywFQ1vuDm+L3N0Lz6Q94amSTZXpqH89F3SF5pDZS84scQW1oij4t3/7N+zduxfFxcU455xzktUuIgDR90fblGBYdwZ0WGQJQ112KFJwGNwwBHQB5FmDpUNDzLYn3Ax4glV2CBX9CO01DnRNBQWnhHJnr3E2i3vo+9xzz8X+/fsxcuTIZLSHqI9oK9OdNhkCAnaLDEWWIsLbqkgY6nJELD4z055ws8imynTZLLi/uCt4e/WMGcS5Ie6g/sEPfoA777wTDzzwACZNmoT8/Mg9ZdybTMkQbWW6u8MfUdzEaVMgIGBTFCiyBMMQrEx2CplWmS6b9Zwv7lkKU9MFDAZxzou74IncY96vdyUrSZKg63riWpcEiS54EtANyJIEhQGQFr23FfUM70DXnnCuYI7OMATmP72ja/7f3ufvucmjYmyVC88umMIXOAkU65GKZD4ZU/Dkr3/9azLakbE8HQG4OwKwyDLsVhl2iwybRYbdojC8ByHWfb3RtpVNry3jnuAYsD56cgkhENB7razWjIyuzEXpEVePWgiB+vp6+P1+nHXWWbBYBnSmR1olukd9zKvC3RGI+jGLHAxtqyLBosiwKd3/p/5xX+/pJbJAScTjzVGIAWEvOTekq0cdc1AfOHAAX/7yl/HBBx8AAIYPH44//OEPmDx5clIbmGipDOr+yJIEa1eA2xQZFqX7/71X3+aa/vb1njBR7fF0S8YLGVYmi43edaRiz0IgAS2z61dT7Ewf1F//+texZ88eLF++HA6HAw8//DA6Ozuxc+fOZLcxocwQ1KdiVWRYFRkWRYI1x3rh3XOmnoh9vUD2zZkONBj5QiY1ei7uCpXNZA1rMv0c9dtvv40XX3wxfN70hRdeiOHDh6O9vb3Pym8auFCR+97CvXBZCvfAQ0Ge6aEVkiv7egfaI2aBkuQQQgTDWDegBljHmswn5qBuaWnBZz7zmfD7VVVVyMvLQ0tLC/dUp4AhBNSADjXKxyyyDKtFgt2iIM+qwGHNzCH0XNjX27NHnGdVYFGCFdX2NnpOW7IzV17IJEuoGAgrdFGmiTmoJUmC1+tFXl5e+DZZltHW1gaPxxO+jfuoU08zDGh+oMOv4ySCPyuHVYbTaoHTrsCaIcPmydzXm8452NDXPuZVsXrzxzjerkI3AHdHIFzu1KbICOjGKXvEufBCZrBCK63Dxy/22JvMHjJlqpiDWgiBMWPG9Llt4sSJ4f9nwj7qXCCEQIdfR4dfx7F2wGaRkW+zIM+mwGHtG4BmEa2ud8hgqoulcxV5z6/dEdDh7gjAEIAsBdcjhGqTq5oBVQM+OOLpt0fMAiXdQgVBAlqwhxyuZ83eMWWhmIOa+6czV3DbiB8nfIAiS8HhcZsCmxLc922WYfJk7OtN5+lQvb+2RZFwwhdceChE8E3uqlEuKUBAM+DpDOCYN9oER/JeyJgZT3giiiOoZ8yYEdcnfvDBB3HLLbeguLg43jZREumGgFfV4FW18G2hleah1eU9t42lWrS63lZZwtgqV9w94HQuvor2tTsC3aNNAsEpC1kKBq4ECXJX2dNQmPeW7QVKuBeZKLqkVSxZuXIlrrnmGgZ1BuhvpbkiS+EqazaLDIscXGme7Ipr0ep6D2ROOZ2Lr6J9bUvXWdmh2BEi+H8JwZ6jIQRkWUJxvrXfz5vIFzLpYhjBXnKga3EXK3YRnVrSgpqvgjOfbnTPdfcUPBNa6t7v3bXqPNQzT4RopUHjlc7FV9G+tkWWw71mgWBIG4YAZEAzBGRJQqHDgrJ8+yk/d6JeyCRa6JQnwwB0IaAbAkbX8YuGCP6r6ywOQhSvzKsBSmnXc2Vtb5IkBYfOLTLsigK7NX17vdO5+Cra13bYZORZFfj8OiCCYW10dasdFhmKLOOc6qI+c8z9rVhP1Ras0M9bN4ILt3RdhIM4FL664BA1UbIwqCmhhBDwa8HhTC+658EVWYqYCw/1xpNZNjWdi6+ifW0JEoa67Dh83AdNAHaLjAqXHQaCW+tcDkufOeZUrVgPlcbUDNG937hrJTV7wETpxaCmlNANAd3Q0Rnou30vVLDFIneVTO36v1WRBhXi6Vx81d/XVmQJTrsCVTOQb1PQoQV79edUF/YJ33hWrAfnuIOPc2iYORS4uiEgIMJz4kIE/x+8X7BXzzOPicwr5qA+cuQIqqurk9KINWvW4Mc//jGampowYcIE/PznP8eUKVP6vf7kyZP4/ve/j5deegnHjx/HmWeeidWrV+PKK69MSvsouUIFW4C+IR6t9rkiS+G3aHoPFf9gzrnhM6pTufiqv4Vf5w0vxrc/PwpFebZ+55h7rhqvKLRDDQh41eBxqkMLrGhu8+Onmz/GmUOc0A2w10uUxWIO6nHjxmHNmjWYO3duTNdffPHFEVXM+vP8889j8eLFWLduHaZOnYrVq1dj1qxZ+Oijj1BeXt7ner/fjy9+8YsoLy/Hiy++iGHDhuFf//oXV5dnqf5WpAPB+XBFkmBRgovbFFnCzn+dwFPvHMAnre3hoeJRQwtw00UjUeK0wd0ZwJB8e8oWX8W68MswBFRNR0AP9oTfP+zGvqY2KLKEA60++DW9RxUzBQUOCw4c9aLusAdjKguS/n0QUfrEfHrW448/jrvuuguXX345fvGLX6C0tDQhDZg6dSouuOACPPbYYwAAwzBQU1ODRYsWYcmSJX2uX7duHX784x/jww8/hNXa/zaWEFVVoardBSQ8Hg9qampMe3oWDdx7B0/g0Tf2wefXUeiwwqpICOgCns4AnDYFi784BhPPKIEkSZClYLGRnoQAFEUKH3xiUYLbqSRJgjAEPmxqw4kOP0ryIsO256fpPaSsi+DKZ6PnEHPXEHRwOkCEh6t7+vsnx/HAn/ai069BIDiULkldn9cQkAA4bBbc86WxuGBEYv4WiejUTH961q233oorrrgCN954I8455xysX78es2fPHtQX9/v92LlzJ5YuXRq+TZZlzJw5E9u3b496nz/+8Y+YNm0abrvtNvzP//wPhg4dirlz5+Kuu+6CovRd2btq1Srcd999g2onmZ8hBJ7bcQg+v46yAhuCEQvYLRLKCmxo9frx3I5DmFBTDBmALgAdfV+jagb6HHzy3sETeG7HIRw61o5A1/B1zZB8zJ1Sg4lnlCTl+3E5rFA1HYYALBYp/P2EqphpWrAH7nKc/sUqEWW2uBaTjRw5Em+++SYee+wxfPWrX8XYsWNhsUR+il27dsX8+VpbW6HrOioqKiJur6iowIcffhj1Pvv378ebb76J6667Dq+++irq6+tx6623IhAIYMWKFX2uX7p0KRYvXhx+P9SjpuxS39yOQ8faUeiwhkMtRIIEl8OKQ8faUd/cHtdQce9eemFXL33/US8efWNfuJeeFKLHv1I/txNR1ot71fe//vUvvPTSSygpKcFXvvKVPkGdbIZhoLy8HE888QQURcGkSZPw6aef4sc//nHUoLbb7bDbT11AgjKfu9OPgCFQqESfd7YpEtqEgLsz9uImcfXSE7zFrK0zALtFgapp0AwBRUa4qpne9b7dqqCtk9MuRNkurpRdv349/uu//gszZ87Enj17MHTo0EF98bKyMiiKgubm5ojbm5ubUVlZGfU+VVVVsFqtEcPcY8eORVNTE/x+P2y27D85iPoqcthglYO9Xbulb2j6dQGrJKHIEfvvR7J66bEoctjgtMlw2m3wdmrw6waMrsVkDouMAocFEIjr+yGizBRzvcfLL78cd911Fx577DG89NJLgw5pALDZbJg0aRI2b94cvs0wDGzevBnTpk2Lep/Pfe5zqK+vh9FjO8q+fftQVVWV0pA2DIGPmtrQ5O6Ez6+xKlOaja7IR82QfHg6AxC9xoQFBNo6A6gZko/RFbEvBAn10q2n6KUH4uylxyr0/QR0geriPFQXOVFZ5EB1kRPVxXkI6CLu74fMxRAC+5q8+Psnx7Gvycu97NSvmHvUuq7j/fffx/DhwxPagMWLF2P+/PmYPHkypkyZgtWrV6O9vR0LFiwAAMybNw/Dhg3DqlWrAAALFy7EY489hu985ztYtGgRPv74Y6xcuRL/+Z//mdB2nY6nM4BZq98Kvy9LgNNmQb5dQb7dggK7Bfld7xfYLcjveiuwW1DQ65oChwX5tuDBF2Y5cjLTyJKEuVNq8Ogb+9Dq9cPlsMKmSPDrwZB22hTMnVIT1xB1Mnrpser5/RxrD34/eRYFfl3gWLt/QN8PmUc6FihS5oo5qN94442kNODaa6/F0aNHsXz5cjQ1NeH888/Hpk2bwgvMDh48CFnu7vjX1NTgtddewx133IHzzjsPw4YNw3e+8x3cddddSWlff9o6tYj3DYEex0dGP0/4dCyy1CPUewS8zYICh9IV/D0+Hg757uvTcTRlOhlCoL65He5OP4ocNnx35mew4e+HcehYO9pEMEhHDS0Y0BNgqFe7/6g3Yo4a6O6ljxpakLRe7cQzSrD4i2PCT+iD/X7IHNK6QJEyUsz7qLOFx+NBUVHRoPdR72tuw5cfexudAXNVhLJb5L5hbwv15pWInn1E799uQYHNAqddyZheWn+9kn+/YDhcdls4vEdX5A/4e+r5pBqtl56KJ9XeL0YG8/1QehlC4K4/1PX74q/V68eooQX40dfG82dsQunaR82gHqQmdwcaT3bCq2po92vwdmrw+jW0qzrau3rY3f/q4Wu6/9WhG+b6EThtSsSQfHevPXrYR/T87RY4rMkfwo+1uEnIYMIu4gVBV6+Ww5Q0EPuavFj+P3XIs1lgt/Qd/erUDHT6Ndz/lfGsOGdCpi94QtFZFRlFTiuKnAMrPCGEgKoZfcI8+P4pwr7rttALgkRGvc+vw+fXcdQ7sCF8WcJp5umVHkP60V4MWGCL8iQWEu+2qcHOB048owQTaopN1atlLzszJWMbIWU/BnWaSZIEh1WBw6pgSMHA9nsbQqDDr0eEeaiH397n/eD/Q7360Mc7opxqNVCGCM7h957Hj4dVkSLD3dbdk/drBj5s9MBmkeHp0KDI3SVBZVmC02bBwVYv6pvb0e4PJGQ+UJYk0/RwUrkQiS8IEiudCxQpc3Hoe5Cypda3bohgaPcYko/am+95W9c1odsCurl+lWyKDIFgLW2bIkOWg4d4yFKwdnZHQMdQlx3/39QzUGC39hnKz7OZb74+3iH/wX4trkxOLM5RZzbOUacIgzp5vSS/ZnQPyUeZp29X9a75+54vACLD3kzT9RIAp10Jz733Xo0fHNrvO2zfc5GePYFb7lL5JJ/KFwS5xgwLFGlgOEdNUSU6VJPZS7JZZJRabCjNH9iwnRACnQEjYtg+ak9e1fB2/TG0dQSgKBIMo/tkqkQGvQC6vraOlraBzdcrsoR8W/8L8ApsFuQ7Iof2e4e9tWvLXaoqpaWzdGou4LY7iheDOk1iCeBEh6rZ929KkoQ8m4I8m4KhOPV8/Ywx0Xslng4/8mwK/uNzIyFBwmN//RhWRYYiS13HSXaFuiEQMIJnPw8rccIwRPiFQKeWuC13uiHg6dTgGcR8vc0iI9+mwCLLOO4LwKbq4Xn54L/B/0sS0B7QsevQccgywi8InDYLlDjO3k5n6dRcYcYFimReDOoBMgyBPUc8+ORYO6yyPPDtPv0EcKJDNdt6Sf31SmrLXeHH0RACf97ThP1HvSh2WqMOFY+tKuwzVKzpBtr9eo8h+x5D9BHb6/SoPf92f2Ln6/2aAX+PFw8dxqkX/j3x1gE8gQMRt+VZlah75/vutbfgyEkfOgI67FYFAd2AIgXPwg4N4WfqymSzLYwz0wJFMjfOUQ/AtvpWPL6lAR81taFT02GRJYwqK8Dcqafv6cYy9zehpjjhc5GZtn8z1ifV012XrvnA0Hx9z7Bv9+vdIR9lSL/3an0zzdcDCK+sl7qO8RpbVYiKIkd4aL+gv+F9e/pL5HJhHCUC56gzxLb6Vtzx+9043u6HEAKGERxy/MfhE/jkmBfLrhzb7x9+rL3aPJsl4UOPmbR/M54n1dP1ShI1H5ioFw6xEkKgI6B3h3dXoO854sYr7zdC1Yzw3LVmCPg1A7IElObbgyv4/Rp8/sRtuQt+b4g4OOL9T93Ap+6Y729VpKiL7vJ718jvEfThevhdtw2kRK7Zp3yITodBHQfDEFj157042qZCAmBRZChycN5T1wWOtwfwi60NePz/mxT1yTnWub+9RzwJD9VM2b+ZjCfVwc4HxvrCIZG9NkkK7gd32iwY6uqer79w1BB89oySiEppDouMmqrCPl9HNwR8vVbfR6y29/fcTx85tH+yIwBvZ2IL6QR0gZMdAZwcxC4Jh0U+ZeGc3mHvtCl48u0DaOvUUFZg6xrGlzJ2yodyE4M6DnWfurGv2QsJgNUiQ4IEIYJDgpIF0DSBA8d82NfsxdmVrj73j7VXKyQkPFTTfcBELJI5jz7Q+cBYXzic6rpHXv8I11xwBqqKHAmZG431hYciB1/8uRwDq5r33sET+M3/HcShY+3wGwIKgDKXA9Nrh6DcZQ/uow+XzNUiev/JKpHbqRno1Pw41h7/yE9oQV+4OE7XMH7d4ZNY+tI/UV3k6H8Ov8cLAgdPuaMUY1DHYffBkwjoBiyyFLVHrMgCmi6w94gnalDH2qs9p6owHKpD8m3wawK6MKBIMmwWaUChmoxjIBPNbKuNY33hcN6w4n6vc9oUNHs6seav9cGtVgmaG03FQqRErEzuWSK39xy8N0qZ3J7XhHr7PlVPaM++ewi/+7P+/ZPjMd9flhAR3n3m43uHfZwlcol6Y1DHQYSen/p7npJ6XddLrL3aMRXB+dOVr+7FJ8fa0XO5nyQBRXnWAYWq2fdvmmUePTTPvOeIG/uPeuGyB/9MOgNG+AWT3dr9wuHNj1qivsDwBXS0eNSudQwC+XYLFEnKqLnRwb4giCyRO7DPESqRG1Hf/lT18Hss2nP7AnB3BBIe9IPdche1RK6ja19977Dv51z7eLbcUWZjUMdhYk0xLLIMXTcgKyJi+EsIAV0Pnil9TlX01eSD6dUKEQzpQX8PJtu/qXSNTuhCmGIevec8sy9ghFdsQwquUQj9HGyKjGKnDQEh0Ozp7PMCQ0DguFeFLgQUBTCM4O+I3apwbjROsiSFAypeoWpuDS1tKM23BXvTRrA4ji4E3B0ahuTb8IWzy+ELlc3t5/S7RG65C+gCJ3wBnPANYr7eKkeEeUHvY2v7CfzQ+2YskUvRMajjMH5YEc6qLMCeIx4EDAMWWQaEgIHgwh0BYGSZE2MqBrcKOTTkaghgRFk+/IEeQ99WCccG+SQfay/JIsuwKFLwTZYhofvFQp+haTn4IkWWpODUQNeFofsIERxoFCL4OCldB2j0NLw4D7/+Pxc+bGxDvs0OSZLCPSEhgrXIz6p04cJRpdCFQEAXCOhGVyGTwT+J9p5ntlmDX9Pf9QStyMEXFgLBudKWtk4U2C2oKHT0eYGhBgT8uhHu9UiSgCLJ4ceORUNSo+eL4xO+QPDFsUWGXxdo7wygxGnFd2d+JqaRDb9m9FmAF7nXPso8fRJL5HYGDHQG/DjmHdgIU0SJXEd/w/hdLwD6uSaRJXKpfwzqOMiyhKVXjA1vz9INgdA2dFkCipxWfHtG7WnD83S92p5ztTIkOKwSgO45rUQ8yUtdgSrLwX8VWYJVlmG1BEPZqkgJ/QPs/lT9f06rRcZtl4zGso11aPH6Uey0wq7IUHUDJ30BuBwW3H7paBRHKVGqGwKaEQztgBYMSc0woOndpUVPVTIg2ny0AYGuLcPBawxAsQAyJEAWCOiALoBLPjMUr3/QHDGloQujq/cd3MJntyiwW7u/dzNth8t2iZrysVlk2Cw2lDgHUSJXM/oP9lMcZdsd/onbcpfoErlR6+H3KpEb7RrrALbc5RoGdZymjy7DT645H49vqceHTW1QNaOr4Ek+5k49I+Y/+lP1ahM5VxvqFVsVGTYlGMRWRTbtH8f00WVYefV4rN3agIYWL9xd25zGVrmwcEYtpo8ui3o/RZagyErwnX6eR4UQXYHe9aYb4V553WF3n3lmf0CgZ1IHRwSCw9qGAShScGTgwDFfnymN0IscXQ+2rbTXmgSzbIfLFWaY8pEkCXlWBXlWBWUDPNJWN7rm63sdbtOneI6/n0V6Ji2RGyqK0zvMex6I03tof6AlcjMRg3oApo8uw4Wjhgy4hOjpxDRXK0sodzlQYLd0H9/Y1TPuOQTde3g5E/R8fI/7/Ch12jCuunDQ34skdQ3jK30/9nGLF4YAnDYFkiR19cKN4H55GdCNYFDruoAsB3vIxflWdAR0uDv9uGBEaUSvLWAIyJIEIQmUF9rhtHZ/UbNsh0s2luxMPEWWUOAIDkMPlKYbUU6y679nH23rXaJL5B7X/DjePvDPEUuJ3GhD96EV+XlWxdRD+AzqAZJlCeOHF6G62JHwYy57rg4fWmCHLAf7YrIkQUCgvV3DOdWFmDFmaEYGcSxCj2+qlDptsFlkaIaAwypDgQSH1dL92CvBCmCFeVY4rDJcdgtUTcAqGeFece9eW6O7E79/Nzicrsiy6bbDJRNLdpqXRZFR5JRR5BzY/nqgb4ncPiVx+znXPhT4Pn9i5+s7Ajo6AjqOegd2f1kCnLbTb69zOSwYWVaA2vJ8nF05+GOSY8WgNgG5q6cXGpK2KhIWXToaK/74Txz3BaLO1S6cUZu1IZ0O46oLUVtegL2NbagslLu2FcmwW2T4/DqMrlFwb6eGdhVo69CgyMC5w4oxdVQpNCM4hB7QjYheW01Jnmm3wyULS3Zmv0QcaRutRG57lIp5/S3Y6wgkbr7eEAi/8IjFvGln4v6vnJuwr386DOoUsyrBJ//g4qLgvHG0wL3k7HKsspwX81xt6DSvRA4V5xJZlrBwRi2WbaxDk0cNvzhyWBR41eATQnDVd/CPOthLlnDpWUNR0uvJKjT37dcMfH5MOaaOHIIPGj044TPHEPBgnWpIO9tOaaPk6K9EbjxCJXKjn1nf/8l2PXv66gDn612DmHoYCAZ1EsmSBLs1GMqOrn/jWfQQ61zttvrWcKAHdAGrIqG2vOCUi6+orz4L2XSBNjXYc7YqMnRDQO86hMVpU6DIMt76uBU3XjQq4mdiUWRYFCDP1j0vPbzUCb3r8Ax/V8/brxnh7WWZ4nRD2marLkfZa7AlcgEgoBv9LsiLViI3OD9vYHiJM4HfyenxmMtBOuZV4VW1rkVcwRXWoR5zKsoEbqtvxbKNdfCqGkqcNtgUGX7dwAlfAAV2BSuvHs+wjlNodGLXv07g53/9GMV5VjisCjoDwS1fFlmGwyqjUzPgUzX84vrJg5pPjxbgmh4syJHuP8+evedGdyd+//eD6AgY/R7RqhkCD/75QwzJt/V7utgxnx9LLj8bF4woTcN3RDRwPOYyQw0psGPIALdaDJZhCKzd2gCvqqGi0A41EDze0CLLqCi0odnjx9qtDbhw1BAOg8chtJDtuM8PCRLsluCK0GAPubuXbFdkuA2B477B7YVW5ODnzkPf5ejBXnzwLdC1Lzw0Fx7aI54svXvPXlWDEAIVhY7wmea9h7RvvGhk2qvLEWUbBnUG23PEg4YWL+wWBf861gFV08MlLu0WBUV5VjS0eLHniCelK6izRanTBqsiwa8bcMh9Q1TVDVhlCaUDLIARC6Vryx2AqEGu6UbwPGrdQEDr3hce0Ae3V7ZPlTYh4OkIQAigxaOiokgKbznrOaQNwPSntBFlGnNWvaCYHPf50e7X0eLpRGdAD68elyUJnYHg7e1+vU+PzzAE6g67sXXfUdQddsPIoDnSVAqtBD/hC/QZghZC4KQvgNryAoyrTt02jd4sigyHVUGhw4oSpw1H21Tsb22Ht1NDVZEDQ112FOVZ4bRZgiVvY9B7QZjdIoe/f0UBdBGsYy56HHVhUyQERDCI506pgdOmoNXrR6dmwOiqyNXq9Wf9tjSiZGCPOoMV51nRGdBhCBE+HxsI9qglBQhoBjoDOorzuhdbcOFZ7PpbCR7aJldgV0yzTS7Wn6vR1fsO9cCD/wbLr4ZEWxCmSHJXGVgJigz4dQNqQHSVt40c0h5TWWDqU9qIMg2DOsOFO3oCkWW0Ra+Po/+FZ3sb27BsYx0XnkUx0JKmqRTPz1WWJTjk4LGTPfUM8D1HPNCM4AlhIXarBJuiQNV0dJ1FA10YAOSoQ9pmKNlJlC0Y1BnsZEcAeVYFHQGBgCFgkbtLU2uGCC9SOtkRiFh4VlnoCJfLc8gKKgtlNHlULjzrR7JKmiZCon6uPQN8xJB8OKzBXyabRQ7XOC9z2dF4sgO6LoKjNpKETs3ot9JaNpTsJDIDBnUGK3XagnVrHQrcHQGomhFeTJZnlVGYZwVE8LrQwrMSp61PTVtJklDs5MKzU0l1SdNYJePnGlmlzR4MXwkoyrNCloBPT3YAAujwa7AqMsZUuDB3yhk4r6Y47dvJiLIRgzqD9XxCPbPUCbVrrtEiy7BbJDS3+TG2yoVx1YX4W30rArqIGM7sKVFbjSi1jvv8Cf+5nmpu3qvqGFach5suHoWaUmfE6IIQXcPnWqiYS3B/eM/5byKKH4M6g/V8Qm1uC57fnG+zQNUNNLf5IxY7mWGrESVesn6uA5mbl6TgnnO7pf/5bzUQXOA42O1jRLmEQZ2BNM3A/77fiE9P+jCs2In7vzIO6/924JRPqNEOnQgJbTUK9b4pcyTz55qoufmIBWyO4G2abqBTM6AG9Kgrz4moG4M6w6x/qwFrtjSgrSOA4JpbwJVnxcIZtfjerLP7fULNpK1GFLtk/1yTNTdvUWQUKDIK7N1PQaFSqqqmQ9WCvW+GNxFrfae7OXFZ/1YDfrTpI+iG6CpsEjzJSdODK7zvuvws3Pz52lN+joj9tl29b+6jznzZ+nMN6MGh8k4OmZMJpKvWN4M6Q2iagckr/wK3LwCbRYIsdS8eMoQBvyZQ5LTi3WUzYTnNYSA8EjM75cLPVTdEV3Dr6OxatJZjT2GURjyUg07pf99vRFtHoKsnHRnEsiTDohho6wjgf99vxNWfHXbKz2XWrUY0OLnwc1VkCfl2C/J7DJmHTh5TGd6UpRjUGeLTkz4YAKIcSAQAkCVA77qOKJfYLDJslu75biEEVM1Ahz94frBf43A5ZTYGdYYYVuyEjOCcdLTRTEMEq5INK07tgeZEZiNJEhzW4CrzknwbAroBn19Hh18P18YnyiQ8PStDzD6vCq48a9cZxJE9BEMEzyZ25Vkx+7yqNLWQ4sETzFLHqsgoyrOissiBEWX5GFaShyH5duTbLeEjRInMjD3qDGGxyLjtklr8aNNH8GsCFsXos+r7tktqT7uQjNKPJ5ilV6goSxGCp8qpWnBVudq1upxbwshsuOo7w/TcRx06MMuVZ8Vtl9SedmsWpV9/J12d6NrzzBPM0s+vGejUgsPkasDgljAK4/asFMm0oI625cYwRERlstnnVbEnnQEMQ2D+0zuwt9ETcdIVEFwA1eRRMbbKhWcXTInYVpUL267MTNMNdHAvN4HbsyiKUw2Rnm4LFpnPQE664jB5+lkUGS5Fhqur/KluiK7gDr5xVTklG7thJhUaIt3b6EG+3YJyV3Dxy97GNizbWIdt9a3pbiLFKZaTrgI9Trri74A5KbKEArsFZQV2DC9xYsSQfFQWOVDstMFuVfq8CCMaLAa1CRmGwNqtDfCqGioLHXBYleDBBlYFlYV2eFUda7c2cKVwhul50lU0PU+64u9A5pBlCU6bBaX5NgwrzsOZpU5UFwdXlhc4LLD288KMKFam+A1as2YNRowYAYfDgalTp2LHjh0x3W/Dhg2QJAlz5sxJbgNTLJ4hUsocoZOuTvgCfSpnhU66qi0vwLjqQv4OZLDQC6oipxXlLgdqSoO97uriPAwpsMPlsMJmkdnzppilPaiff/55LF68GCtWrMCuXbswYcIEzJo1Cy0tLae83yeffII777wTF198cYpamjrxDpFSZgiddFVgV9DkUdER0GF0zXc2edSIk674O5BdwuGdZ8VQV2jI3IlhJXkoc9lRwD3ddAppD+pHH30UN998MxYsWIBzzjkH69atg9PpxFNPPdXvfXRdx3XXXYf77rsPo0aNSmFrUyOeIVLKLNNHl2Hl1eMxtsoFn6qhxavCp2oYW+WK2JrF34HsJ0kS7BYFhQ4rygsdOHNIVzEW9rqpl7Su+vb7/di5cyeWLl0avk2WZcycORPbt2/v9373338/ysvLceONN+Jvf/vbKb+GqqpQVTX8vsdj/qHC0BDp3sY2VBbKfbbxnPQFMLbKhXHV5t9eRn1NH12GC0cNOeWWK/4O5KZQMZaQUN3y4KEjwX956EjuSWuPurW1Fbquo6KiIuL2iooKNDU1Rb3P22+/jV/+8pdYv359TF9j1apVKCoqCr/V1NQMut3JFs8QKWWm0ElXM8YMxfjhRX1+lvwdIKC7bnmhIzhkPqw4LzxkPtRlR1GeNbjQkD3vrJb2oe94tLW14frrr8f69etRVhbbHtKlS5fC7XaH3w4dOpTkViZGrEOklL34O0DRhIbMXQ4rhhTYUV2chxFl+Rhe4mR4Z6m0Dn2XlZVBURQ0NzdH3N7c3IzKyso+1zc0NOCTTz7B7Nmzw7cZXXV5LRYLPvroI9TWRpbRtNvtsNvtSWh98k0fXYYpI0pZhSyHxTJMTgR0H/fZU8+zukPD5zw9LPOkNahtNhsmTZqEzZs3h7dYGYaBzZs34/bbb+9z/dlnn426urqI2+6++260tbXhpz/9aUYMa8cjWlWql947zKpUOSY0TE4Ur95ndQPBQ0hUzWAt8wyS9hKiixcvxvz58zF58mRMmTIFq1evRnt7OxYsWAAAmDdvHoYNG4ZVq1bB4XDg3HPPjbh/cXExAPS5PdOFqlJ5OvywKgokBEsX7vnUjWUb6zj0SUQDElqwVugInh6mGyJ4EElXr9uvMbzNJu1Bfe211+Lo0aNYvnw5mpqacP7552PTpk3hBWYHDx6ELOfWUG+oKlWLpxOdmgFDaOGPyRLQGTCwdmsDLhw1hEOgRDQoiiwhz6Ygz9a92twwRHCoXDPCw+cBjcPm6cLTs0yo7rAb1z25HZ5Ovd9rCh0KfnvTNA6JElHKBLp63P4eW8Zy6fxunp5FYS3eTrT1COmeizdDL6vaOnW0eDsBMKiJKDWsigyrIiO/x/pc3RBQte5jQFXu8044BrUJ7TnsQc9f82i/86LrusvOruj7QSKiFFG6DiUJFckTQqAzYISPAmVwDx6D2oRi3f7IbZJEZDaSFDnnzeAePAa1CQ0vcUICcKpfZanrOiIiM+svuEOhrWo6dB7XekoMahO66txK/PeLErRT/PIqsoSrzu1bFIaIyMx6BzcQXKSmasGV5dwi1heD2oQ+avHCaVPg6ezeltW7h+20KfioxctV3xnAMAQrixGdQmiRGnotUgutMFc1HR2B3O15M6hN6LjPD7tFQYVLwVGvCkN0h7QsAUML7DC6riNzi1Zdrra8gNXliE4jcn93sDhLZ0BHhz8Y2rk0182gNqHQWcSSBORZFXQGDAgISJDgsMpQFAmKAM8iNrlQdTmvqqHEaYNNkeHXDextbGN1OaIBcFgVOKwKStB9BKjaY6FathZkYVCb0LjqQgwpsGHPEQ8kCbAoMiRIEAA6NR0dbh3jqgt5FrGJharLeVUNlYWO8HnSDllBZaGMJo/K6nJEgxA6AtRhVVDUo8cdXqSWRcVYGNRmF3qBGJqkzs4XjFlnzxEPGlq8KHHawiEdIkkSip1WNLR4seeIh+sMiBIkFNwhoWIsasBAZ9e/mdjrZlCb0J4jHhzz+lFVlAd3RwCqpkMYwX3TeTYLivKsOOb180nexI77/AjoAjYlep16uyLDbQiuMyBKot7FWACETw3r1IK970xYoMagNqHQk3y5y4aSfCs6/cEhHIssw2GTIQygxavySd7EQusM/LoBh6z0+biqG7DKEtcZEKVY7+Fyvxac41YDwTKoZhwuZ1CbUO8n+eCqx+4n+05d55O8yY2rLkRteQH2NrahslCOGP4WQuCkL4CxVS6uMyBKs9CZ3cgLBndA71FFzSTndefW+ZEZIvQkf8IX6LP9IPQkX1tewCd5E5NlCQtn1KLArqDJo6IjoMMwBDoCOpo8KgrsChbOqOVCMiKTsSoyCh1WlLscqCl14oxSJ4a67HA5rLAq6fl7ZVCbEJ/ks8P00WVYefV4jK1ywadqaPGq8Kkaxla5uDWLKENYFBkuhxVDXfa0lW3medQmFlEswxCwyiyWkYlYmYyIBoNBbXJ8kiciym1cTGZysixxCxYRUQ7jHDUREZGJMaiJiIhMjEFNRERkYgxqIiIiE2NQExERmRiDmoiIyMQY1ERERCbGoCYiIjIxBjUREZGJMaiJiIhMjEFNRERkYgxqIiIiE2NQExERmRiDmoiIyMQY1ERERCbGoCYiIjIxBjUREZGJMaiJiIhMjEFNRERkYgxqIiIiE2NQExERmRiDmoiIyMQs6W4AEdFgGIbAniMeHPf5Ueq0YVx1IWRZSneziBKGQU1EGWtbfSvWbm1AQ4sXAV3AqkioLS/Awhm1mD66LN3NI0oIDn0TUUbaVt+KZRvrsLfRg3y7BeUuO/LtFuxtbMOyjXXYVt+a7iYSJQSDmogyjmEIrN3aAK+qobLQAYdVgSxLcFgVVBba4VV1rN3aAMMQ6W4q0aAxqIko4+w54kFDixclThskKXI+WpIkFDutaGjxYs8RT5paSJQ4DGoiyjjHfX4EdAGbEv0pzK7ICBgCx33+FLeMKPEY1ESUcUqdNlgVCX7diPpxVTdglSWUOm0pbhlR4jGoiSjjjKsuRG15AU74AhAich5aCIGTvgBqywswrrowfLthCNQddmPrvqOoO+zm/DVlDFME9Zo1azBixAg4HA5MnToVO3bs6Pfa9evX4+KLL0ZJSQlKSkowc+bMU15PRNlHliUsnFGLAruCJo+KjoAOwxDoCOho8qgosCtYOKM2vJ96W30r5j+9A9/+9bu48/f/wLd//S7mP72DK8MpI6Q9qJ9//nksXrwYK1aswK5duzBhwgTMmjULLS0tUa/fsmULvvnNb+Kvf/0rtm/fjpqaGvzbv/0bPv300xS3nIjSafroMqy8ejzGVrngUzW0eFX4VA1jq1xYefX48D5qbuOiTCeJ3uNGKTZ16lRccMEFeOyxxwAAhmGgpqYGixYtwpIlS057f13XUVJSgsceewzz5s3r83FVVaGqavh9j8eDmpoauN1uFBYW9rmeiDLLqSqTGYbA/Kd3YG+jB5WFjogV4kIINHlUjK1y4dkFU1jNjEwrrT1qv9+PnTt3YubMmeHbZFnGzJkzsX379pg+h8/nQyAQQGlpadSPr1q1CkVFReG3mpqahLSdiMxBliWMH16EGWOGYvzwoojA5TYuygZpDerW1lbouo6KioqI2ysqKtDU1BTT57jrrrtQXV0dEfY9LV26FG63O/x26NChQbebiDIDt3FRNsjoWt8PPvggNmzYgC1btsDhcES9xm63w263p7hlRGQGPbdxOWSlz8e5jYsyQVp71GVlZVAUBc3NzRG3Nzc3o7Ky8pT3ffjhh/Hggw/i9ddfx3nnnZfMZhJRhhrINi4is0lrUNtsNkyaNAmbN28O32YYBjZv3oxp06b1e7+HHnoIDzzwADZt2oTJkyenoqlElIHi3cZFZEZpH/pevHgx5s+fj8mTJ2PKlClYvXo12tvbsWDBAgDAvHnzMGzYMKxatQoA8KMf/QjLly/Hc889hxEjRoTnsgsKClBQUJC274OIzCm0jSt0HKbbELDKEsZWuXgcJsUsneeepz2or732Whw9ehTLly9HU1MTzj//fGzatCm8wOzgwYOQ5e6O/9q1a+H3+/H1r3894vOsWLEC9957byqbTkQZYvroMlw4akjanmgps6X73PO076NONY/Hg6KiIu6jJiKi0woVzPGqGkqcNtgUGX7dwAlfAAV2JaK4TrKkvTIZERGRGZnl3HMGNRERURRmKZjDoCYiIorCLAVz0r6YjIgoU6VzJTAln1kK5jCoiYh6iDV8070SmJIvVDBnb2MbKgvlPoe6nPQFMLbKlfSCOVz1TUTUJdbwNcNKYEqM070w6/5Z6yh2WmFXZKi6gZMp/FkzqImIEHv48ujM7BHPC7PwdV0Fc1I5esKhbyLKeb234YTC1yErqCyU0eRRsXZrQ7hoSqwrgccPL0rHt0Mx6O+F2d7GNizbWBfRU053wRwGNRHlrNCw586DJ/BhYxuKndbThm8sK4HdPDrT1OJ5YRYK49C55+nAoCainNRzOLNd1dGmBuDzaygvdKDAHvnU2DN8zbISmAYu00ZFuI+aiHJOaNhzb6MH+XYLhhTYIEsSOgM6Pj3RAa+qRVzfM3x5dGbmM8v+6FgxqIkop0QrC+m0KXBYZUACdMPA0TYVAsEQ7h2+PDoz8/UcFYnGbKMiDGoiyinRhj0lScJQlwOKFHxK7Axo8Kl6v+EbOjpzbJULPlVDi1eFT9UwtsrFrVkZINNGRThHTUQ5pb9hzwK7BcNK8tDi6URHQMexdj/ybUq/51aneyUwDVxoVGTZxjo0edSo+6PNNCrCoCainHKqxWAFdgvkIgfcHQEsuvQz+OyZJacM33SuBKbBCY2KhBYUurv2R/f3wiydGNRElFNOVxbS3aFhbFUhrp92pml6VJQcmTIqwjlqIsopXAxGPYVGRWaMGYrxw4tM+XNnUBNRzuFiMMokrPVNRDmLx1SaF3823ThHTUQ5i4vBzIlHiEbi0DcREZlG76px5S478u2W8GEZ2+pb093ElGNQExGRKUSrGifLEhxWBZWFdnhVHWu3NsAwcmrGlkFNRETmEM9hGbmEQU1ERKaQaYdlpAoXkxERZYlMXynNI0SjY1ATEWWBbFgpfbqqcSd9AYytcpnmsIxU4dA3EVGGy5aV0qwaFx2Dmogog2XbSmlWjeuLQ99ERANkhjnheFZKZ0pxl0w5LCNVGNRERANgljnhWFZKuzNwpTSrxnXj0DcRUZzMNCfcc6V0NLm6UjqbMKiJiOJgtjnh0ErpE74Aep+xFFopXVtekHMrpbMJg5qIKA5mq57FldLZj0FNRBQHM1bP4krp7MbFZEREcTBr9SyulM5eDGoiojiYuXoWV0pnJw59ExHFgXPClGoMaiKiOHFOmFJJEr3X82c5j8eDoqIiuN1uFBZyuwIRDZwZKpNR9uMcNRHRAHFOmFKBQ99EREQmxqAmIiIyMQY1ERGRiTGoiYiITIxBTUREZGIMaiIiIhNjUBMREZkYg5qIiMjETBHUa9aswYgRI+BwODB16lTs2LHjlNe/8MILOPvss+FwODB+/Hi8+uqrKWopERFRaqU9qJ9//nksXrwYK1aswK5duzBhwgTMmjULLS0tUa/ftm0bvvnNb+LGG2/Ee++9hzlz5mDOnDn45z//meKWExERJV/aa31PnToVF1xwAR577DEAgGEYqKmpwaJFi7BkyZI+11977bVob2/Hn/70p/BtF154Ic4//3ysW7euz/WqqkJV1fD7Ho8HNTU1rPVNREQZIa09ar/fj507d2LmzJnh22RZxsyZM7F9+/ao99m+fXvE9QAwa9asfq9ftWoVioqKwm81NTWJ+waIiIiSLK2HcrS2tkLXdVRUVETcXlFRgQ8//DDqfZqamqJe39TUFPX6pUuXYvHixeH33W43zjjjDHg8nkG2noiIaHBcLhck6dQnrmX96Vl2ux12uz38fiig2bMmIqJ0i2UaNq1BXVZWBkVR0NzcHHF7c3MzKisro96nsrIyrut7q66uxqFDh2J6FXM6ofnuQ4cOcb57gPgYDg4fv8Hh4zc4fPwGz+VynfaatAa1zWbDpEmTsHnzZsyZMwdAcDHZ5s2bcfvtt0e9z7Rp07B582Z897vfDd/2xhtvYNq0aTF9TVmWMXz48ME2PUJhYSF/SQeJj+Hg8PEbHD5+g8PHL7nSPvS9ePFizJ8/H5MnT8aUKVOwevVqtLe3Y8GCBQCAefPmYdiwYVi1ahUA4Dvf+Q5mzJiBRx55BFdddRU2bNiAd999F0888UQ6vw0iIqKkSHtQX3vttTh69CiWL1+OpqYmnH/++di0aVN4wdjBgwchy92L06dPn47nnnsOd999N5YtW4bPfOYzePnll3Huueem61sgIiJKmrQHNQDcfvvt/Q51b9mypc9t3/jGN/CNb3wjya06PbvdjhUrVkQsVqP48DEcHD5+g8PHb3D4+KVG2gueEBERUf/SXkKUiIiI+segJiIiMjEGNRERkYkxqImIiEyMQX0aPCt78OJ5DNevX4+LL74YJSUlKCkpwcyZM0/7mGe7eH8HQzZs2ABJksLFhHJVvI/fyZMncdttt6Gqqgp2ux1jxozJ6b/jeB+/1atX46yzzkJeXh5qampwxx13oLOzM0WtzVKC+rVhwwZhs9nEU089Jfbs2SNuvvlmUVxcLJqbm6Ne/8477whFUcRDDz0kPvjgA3H33XcLq9Uq6urqUtxy84j3MZw7d65Ys2aNeO+998TevXvFDTfcIIqKisThw4dT3HJziPfxCzlw4IAYNmyYuPjii8VXvvKV1DTWhOJ9/FRVFZMnTxZXXnmlePvtt8WBAwfEli1bxO7du1PccnOI9/H77W9/K+x2u/jtb38rDhw4IF577TVRVVUl7rjjjhS3PLswqE9hypQp4rbbbgu/r+u6qK6uFqtWrYp6/TXXXCOuuuqqiNumTp0qvv3tbye1nWYW72PYm6ZpwuVyiWeffTZZTTS1gTx+mqaJ6dOniyeffFLMnz8/p4M63sdv7dq1YtSoUcLv96eqiaYW7+N32223iS984QsRty1evFh87nOfS2o7sx2HvvuRirOys91AHsPefD4fAoEASktLk9VM0xro43f//fejvLwcN954YyqaaVoDefz++Mc/Ytq0abjttttQUVGBc889FytXroSu66lqtmkM5PGbPn06du7cGR4e379/P1599VVceeWVKWlztjJFZTIzSsVZ2dluII9hb3fddReqq6v7vADKBQN5/N5++2388pe/xO7du1PQQnMbyOO3f/9+vPnmm7juuuvw6quvor6+HrfeeisCgQBWrFiRimabxkAev7lz56K1tRUXXXQRhBDQNA233HILli1bloomZy32qMm0HnzwQWzYsAEbN26Ew+FId3NMr62tDddffz3Wr1+PsrKydDcnIxmGgfLycjzxxBOYNGkSrr32Wnz/+9/HunXr0t20jLBlyxasXLkSjz/+OHbt2oWXXnoJr7zyCh544IF0Ny2jsUfdj3SclZ1tBvIYhjz88MN48MEH8Ze//AXnnXdeMptpWvE+fg0NDfjkk08we/bs8G2GYQAALBYLPvroI9TW1ia30SYykN+/qqoqWK1WKIoSvm3s2LFoamqC3++HzWZLapvNZCCP3z333IPrr78eN910EwBg/PjxaG9vx7e+9S18//vfjzhgiWLHR60fPc/KDgmdld3f2dehs7J7iues7GwzkMcQAB566CE88MAD2LRpEyZPnpyKpppSvI/f2Wefjbq6OuzevTv89uUvfxmXXnopdu/ejZqamlQ2P+0G8vv3uc99DvX19eEXOACwb98+VFVV5VRIAwN7/Hw+X58wDr3oETxWYuDSvZrNzDZs2CDsdrt45plnxAcffCC+9a1vieLiYtHU1CSEEOL6668XS5YsCV//zjvvCIvFIh5++GGxd+9esWLFCm7PivMxfPDBB4XNZhMvvviiaGxsDL+1tbWl61tIq3gfv95yfdV3vI/fwYMHhcvlErfffrv46KOPxJ/+9CdRXl4ufvCDH6TrW0ireB+/FStWCJfLJX73u9+J/fv3i9dff13U1taKa665Jl3fQlZgUJ/Gz3/+c3HGGWcIm80mpkyZIv7f//t/4Y/NmDFDzJ8/P+L63//+92LMmDHCZrOJcePGiVdeeSXFLTafeB7DM888UwDo87ZixYrUN9wk4v0d7CnXg1qI+B+/bdu2ialTpwq73S5GjRolfvjDHwpN01LcavOI5/ELBALi3nvvFbW1tcLhcIiamhpx6623ihMnTqS+4VmEx1wSERGZGOeoiYiITIxBTUREZGIMaiIiIhNjUBMREZkYg5qIiMjEGNREREQmxqAmIiIyMQY1ERGRiTGoiYiITIxBTZRlbrjhBsyZM2dA933mmWdQXFyc0PYQ0eAwqImIiEyMQU2UQx599FGMHz8e+fn5qKmpwa233gqv1wsA2LJlCxYsWAC32w1JkiBJEu69914AgKqquPPOOzFs2DDk5+dj6tSp2LJlS/jzhnrir732GsaOHYuCggJcfvnlaGxsjPj6Tz31FMaNGwe73Y6qqircfvvtAID/+I//wJe+9KWIawOBAMrLy/HLX/4yeQ8IUQZgUBPlEFmW8bOf/Qx79uzBs88+izfffBPf+973AADTp0/H6tWrUVhYiMbGRjQ2NuLOO+8EANx+++3Yvn07NmzYgPfffx/f+MY3cPnll+Pjjz8Of26fz4eHH34Yv/71r/HWW2/h4MGD4fsDwNq1a3HbbbfhW9/6Furq6vDHP/4Ro0ePBgDcdNNN2LRpU0Sw/+lPf4LP58O1116bioeGyLzSfXwXESVWPEdbvvDCC2LIkCHh959++mlRVFQUcc2//vUvoSiK+PTTTyNuv+yyy8TSpUvD9wMg6uvrwx9fs2aNqKioCL9fXV0tvv/97/fblnPOOUf86Ec/Cr8/e/ZsccMNN8T0fRBlM0u6XygQUer85S9/wapVq/Dhhx/C4/FA0zR0dnbC5/PB6XRGvU9dXR10XceYMWMibldVFUOGDAm/73Q6UVtbG36/qqoKLS0tAICWlhYcOXIEl112Wb9tu+mmm/DEE0/ge9/7Hpqbm/HnP/8Zb7755mC+XaKswKAmyhGffPIJvvSlL2HhwoX44Q9/iNLSUrz99tu48cYb4ff7+w1qr9cLRVGwc+dOKIoS8bGCgoLw/61Wa8THJEmC6DruPi8v77TtmzdvHpYsWYLt27dj27ZtGDlyJC6++OJ4v02irMOgJsoRO3fuhGEYeOSRRyDLweUpv//97yOusdls0HU94raJEydC13W0tLQMODhdLhdGjBiBzZs349JLL416zZAhQzBnzhw8/fTT2L59OxYsWDCgr0WUbRjURFnI7XZj9+7dEbeVlZUhEAjg5z//OWbPno133nkH69ati7hmxIgR8Hq92Lx5MyZMmACn04kxY8bguuuuw7x58/DII49g4sSJOHr0KDZv3ozzzjsPV111VUxtuvfee3HLLbegvLwcV1xxBdra2vDOO+9g0aJF4WtuuukmfOlLX4Ku65g/f/6gHweirJDuSXIiSqz58+cLAH3ebrzxRvHoo4+KqqoqkZeXJ2bNmiV+9atfCQDixIkT4fvfcsstYsiQIQKAWLFihRBCCL/fL5YvXy5GjBghrFarqKqqEldffbV4//33hRDRF6Ft3LhR9H6KWbdunTjrrLPCn2PRokURHzcMQ5x55pniyiuvTPjjQpSpJCG6JpGIiNLM6/Vi2LBhePrpp/HVr3413c0hMgUOfRNR2hmGgdbWVjzyyCMoLi7Gl7/85XQ3icg0GNRElHYHDx7EyJEjMXz4cDzzzDOwWPjURBTCoW8iIiITYwlRIiIiE2NQExERmRiDmoiIyMQY1ERERCbGoCYiIjIxBjUREZGJMaiJiIhMjEFNRERkYv8/3WTlr3VTP+MAAAAASUVORK5CYII="},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"markdown","source":"# **KNN Regression Model**","metadata":{}},{"cell_type":"markdown","source":"> **Create and Train the Model :**","metadata":{}},{"cell_type":"code","source":"from sklearn.neighbors import KNeighborsRegressor","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.429756Z","iopub.execute_input":"2023-09-04T15:18:03.430838Z","iopub.status.idle":"2023-09-04T15:18:03.435207Z","shell.execute_reply.started":"2023-09-04T15:18:03.430802Z","shell.execute_reply":"2023-09-04T15:18:03.434236Z"},"trusted":true},"execution_count":247,"outputs":[]},{"cell_type":"code","source":"knn_regr = KNeighborsRegressor(n_neighbors=5)\nknn_regr.fit(x_train, y_train)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.436303Z","iopub.execute_input":"2023-09-04T15:18:03.436951Z","iopub.status.idle":"2023-09-04T15:18:03.455872Z","shell.execute_reply.started":"2023-09-04T15:18:03.436917Z","shell.execute_reply":"2023-09-04T15:18:03.454605Z"},"trusted":true},"execution_count":248,"outputs":[{"execution_count":248,"output_type":"execute_result","data":{"text/plain":"KNeighborsRegressor()","text/html":"
KNeighborsRegressor()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Predict Test Set Results :**","metadata":{}},{"cell_type":"code","source":"x_test.drop('Y_Predicted', axis=1, inplace=True)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.457503Z","iopub.execute_input":"2023-09-04T15:18:03.457950Z","iopub.status.idle":"2023-09-04T15:18:03.467417Z","shell.execute_reply.started":"2023-09-04T15:18:03.457912Z","shell.execute_reply":"2023-09-04T15:18:03.466336Z"},"trusted":true},"execution_count":249,"outputs":[]},{"cell_type":"code","source":"knn_y_pred = svr.predict(x_test)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.468783Z","iopub.execute_input":"2023-09-04T15:18:03.469409Z","iopub.status.idle":"2023-09-04T15:18:03.480834Z","shell.execute_reply.started":"2023-09-04T15:18:03.469374Z","shell.execute_reply":"2023-09-04T15:18:03.479947Z"},"trusted":true},"execution_count":250,"outputs":[]},{"cell_type":"markdown","source":"> **Evaluation of Model Performance :**","metadata":{}},{"cell_type":"code","source":"knn_r2 = r2_score(y_test, knn_y_pred)\nknn_r2","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.482430Z","iopub.execute_input":"2023-09-04T15:18:03.483493Z","iopub.status.idle":"2023-09-04T15:18:03.493469Z","shell.execute_reply.started":"2023-09-04T15:18:03.483458Z","shell.execute_reply":"2023-09-04T15:18:03.492299Z"},"trusted":true},"execution_count":251,"outputs":[{"execution_count":251,"output_type":"execute_result","data":{"text/plain":"0.5166550618405741"},"metadata":{}}]},{"cell_type":"code","source":"knn_mse = mean_squared_error(y_test, knn_y_pred)\nknn_mse","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.495011Z","iopub.execute_input":"2023-09-04T15:18:03.495582Z","iopub.status.idle":"2023-09-04T15:18:03.511653Z","shell.execute_reply.started":"2023-09-04T15:18:03.495551Z","shell.execute_reply":"2023-09-04T15:18:03.510785Z"},"trusted":true},"execution_count":252,"outputs":[{"execution_count":252,"output_type":"execute_result","data":{"text/plain":"0.035262344389530756"},"metadata":{}}]},{"cell_type":"code","source":"knn_rmse = np.sqrt(knn_mse)\nknn_rmse","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.513244Z","iopub.execute_input":"2023-09-04T15:18:03.513688Z","iopub.status.idle":"2023-09-04T15:18:03.523592Z","shell.execute_reply.started":"2023-09-04T15:18:03.513658Z","shell.execute_reply":"2023-09-04T15:18:03.522452Z"},"trusted":true},"execution_count":253,"outputs":[{"execution_count":253,"output_type":"execute_result","data":{"text/plain":"0.1877827052460656"},"metadata":{}}]},{"cell_type":"markdown","source":"> **Visualize the Results of the Prediction :**","metadata":{}},{"cell_type":"code","source":"# Plot Actual vs Predicted Values\n\nplt.scatter(y_test, knn_y_pred)\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:03.526551Z","iopub.execute_input":"2023-09-04T15:18:03.526929Z","iopub.status.idle":"2023-09-04T15:18:04.402907Z","shell.execute_reply.started":"2023-09-04T15:18:03.526899Z","shell.execute_reply":"2023-09-04T15:18:04.401619Z"},"trusted":true},"execution_count":254,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"# Scatter Plots of each feature vs predicted value with regression line\n\nlin_regressor_plot = x_test\nlin_regressor_plot['Y_Predicted'] = knn_y_pred\n\nsns.lmplot(x='Signal_Strength', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Latency', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Required_Bandwidth', y='Y_Predicted', data=lin_regressor_plot)\n\nsns.lmplot(x='Allocated_Bandwidth', y='Y_Predicted', data=lin_regressor_plot)\n\nplt.tight_layout()\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:04.404879Z","iopub.execute_input":"2023-09-04T15:18:04.405588Z","iopub.status.idle":"2023-09-04T15:18:06.383363Z","shell.execute_reply.started":"2023-09-04T15:18:04.405540Z","shell.execute_reply":"2023-09-04T15:18:06.382233Z"},"trusted":true},"execution_count":255,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/opt/conda/lib/python3.10/site-packages/seaborn/axisgrid.py:118: UserWarning: The figure layout has changed to tight\n self._figure.tight_layout(*args, **kwargs)\n/tmp/ipykernel_32/1444102090.py:14: UserWarning: The figure layout has changed to tight\n plt.tight_layout()\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"markdown","source":"# **Comparing Results of MLR, SVM and KNN Regression Models**","metadata":{}},{"cell_type":"code","source":"# Create the plot with multiple lines to compare measures like: mse, rmse and r2_score\n\ncategories = ['MLR', 'SVR', 'KNN']\nx = np.arange(len(categories))\nr2_scores = [lin_regressor_r2, svr_r2, knn_r2]\nmse_scores = [lin_regressor_mse, svr_mse, knn_mse]\nrmse_scores = [lin_regressor_rmse, svr_rmse, knn_rmse]\n\nwidth = 0.25\nfig, ax = plt.subplots()\n\nax.bar(x, r2_scores, label='R2 Scores', width=0.25)\nax.bar(x+width, mse_scores, label='MSE', width=0.25)\nax.bar(x+2*width, rmse_scores, label='RMSE', width=0.25)\n\n# Customize the plot\nplt.xlabel('Model Names')\nplt.ylabel('Score')\nplt.title('Compare Evaluation Metrics of MLR, SVR and KNN')\nplt.legend() # Show legend with labels\nax.set_xticks(x)\nax.set_xticklabels(categories)\n\n# Show the plot\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:06.384941Z","iopub.execute_input":"2023-09-04T15:18:06.385621Z","iopub.status.idle":"2023-09-04T15:18:06.689102Z","shell.execute_reply.started":"2023-09-04T15:18:06.385588Z","shell.execute_reply":"2023-09-04T15:18:06.687923Z"},"trusted":true},"execution_count":256,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}]},{"cell_type":"code","source":"# Thus, we can conclude that, SVR and KNN Regressor has similar performance\n# Which is better than MLR(Multliple Linear Regression)","metadata":{"execution":{"iopub.status.busy":"2023-09-04T15:18:06.690251Z","iopub.execute_input":"2023-09-04T15:18:06.690991Z","iopub.status.idle":"2023-09-04T15:18:06.695836Z","shell.execute_reply.started":"2023-09-04T15:18:06.690946Z","shell.execute_reply":"2023-09-04T15:18:06.694665Z"},"trusted":true},"execution_count":257,"outputs":[]}]} \ No newline at end of file diff --git a/49. Day 49 - Capstone Project - 5G Resources - MLR, SVR, KNN_R/5g-quality-of-service-all-regression-algorithms.pdf b/49. 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