-
Notifications
You must be signed in to change notification settings - Fork 0
/
A1 10 Final Model Developed.rmp
229 lines (229 loc) · 14.9 KB
/
A1 10 Final Model Developed.rmp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
<?xml version="1.0" encoding="UTF-8"?><process version="9.6.000">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.6.000" expanded="true" name="Process">
<parameter key="logverbosity" value="init"/>
<parameter key="random_seed" value="2001"/>
<parameter key="send_mail" value="never"/>
<parameter key="notification_email" value=""/>
<parameter key="process_duration_for_mail" value="30"/>
<parameter key="encoding" value="SYSTEM"/>
<process expanded="true">
<operator activated="true" class="retrieve" compatibility="9.6.000" expanded="true" height="68" name="Retrieve AirBnB Full" width="90" x="45" y="34">
<parameter key="repository_entry" value="AirBnB Full"/>
</operator>
<operator activated="true" class="filter_examples" compatibility="9.6.000" expanded="true" height="103" name="Filter Examples" width="90" x="45" y="136">
<parameter key="parameter_expression" value=""/>
<parameter key="condition_class" value="custom_filters"/>
<parameter key="invert_filter" value="false"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="reviews_per_month.is_not_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
<operator activated="true" class="discretize_by_user_specification" compatibility="9.6.000" expanded="true" height="103" name="Discretize" width="90" x="45" y="238">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="single"/>
<parameter key="attribute" value="reviews_per_month"/>
<parameter key="attributes" value=""/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="numeric"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="real"/>
<parameter key="block_type" value="value_series"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_series_end"/>
<parameter key="invert_selection" value="false"/>
<parameter key="include_special_attributes" value="false"/>
<list key="classes">
<parameter key="viable " value="1.0"/>
<parameter key="unviable" value="Infinity"/>
</list>
</operator>
<operator activated="true" class="set_role" compatibility="9.6.000" expanded="true" height="82" name="Set Role" width="90" x="179" y="34">
<parameter key="attribute_name" value="reviews_per_month"/>
<parameter key="target_role" value="label"/>
<list key="set_additional_roles"/>
</operator>
<operator activated="true" class="operator_toolbox:smote" compatibility="2.3.000" expanded="true" height="82" name="SMOTE Upsampling" width="90" x="179" y="136">
<parameter key="number_of_neighbours" value="5"/>
<parameter key="normalize" value="true"/>
<parameter key="equalize_classes" value="true"/>
<parameter key="upsampling_size" value="1000"/>
<parameter key="auto_detect_minority_class" value="true"/>
<parameter key="round_integers" value="true"/>
<parameter key="nominal_change_rate" value="0.5"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="2020"/>
</operator>
<operator activated="true" class="select_attributes" compatibility="9.6.000" expanded="true" height="82" name="Select Attributes" width="90" x="179" y="238">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value="|calculated_host_listings_count|id|number_of_reviews|price|reviews_per_month|room_type|viability "/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="attribute_value"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="time"/>
<parameter key="block_type" value="attribute_block"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_matrix_row_start"/>
<parameter key="invert_selection" value="true"/>
<parameter key="include_special_attributes" value="false"/>
</operator>
<operator activated="true" class="weight_by_information_gain" compatibility="9.6.000" expanded="true" height="82" name="Weight by Information Gain" width="90" x="313" y="34">
<parameter key="normalize_weights" value="false"/>
<parameter key="sort_weights" value="true"/>
<parameter key="sort_direction" value="descending"/>
</operator>
<operator activated="true" class="select_by_weights" compatibility="9.6.000" expanded="true" height="103" name="Select by Weights" width="90" x="380" y="187">
<parameter key="weight_relation" value="top k"/>
<parameter key="weight" value="1.0"/>
<parameter key="k" value="8"/>
<parameter key="p" value="0.5"/>
<parameter key="deselect_unknown" value="true"/>
<parameter key="use_absolute_weights" value="true"/>
</operator>
<operator activated="true" class="sample_stratified" compatibility="9.6.000" expanded="true" height="82" name="Sample (Stratified)" width="90" x="447" y="34">
<parameter key="sample" value="absolute"/>
<parameter key="sample_size" value="10000"/>
<parameter key="sample_ratio" value="0.1"/>
<parameter key="use_local_random_seed" value="true"/>
<parameter key="local_random_seed" value="2020"/>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="9.6.000" expanded="true" height="145" name="Cross Validation (2)" width="90" x="581" y="136">
<parameter key="split_on_batch_attribute" value="false"/>
<parameter key="leave_one_out" value="false"/>
<parameter key="number_of_folds" value="10"/>
<parameter key="sampling_type" value="automatic"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="2020"/>
<parameter key="enable_parallel_execution" value="true"/>
<process expanded="true">
<operator activated="true" class="h2o:gradient_boosted_trees" compatibility="9.3.001" expanded="true" height="103" name="Gradient Boosted Trees (2)" width="90" x="112" y="34">
<parameter key="number_of_trees" value="80"/>
<parameter key="reproducible" value="false"/>
<parameter key="maximum_number_of_threads" value="4"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="maximal_depth" value="10"/>
<parameter key="min_rows" value="10.0"/>
<parameter key="min_split_improvement" value="0.0"/>
<parameter key="number_of_bins" value="20"/>
<parameter key="learning_rate" value="0.01"/>
<parameter key="sample_rate" value="1.0"/>
<parameter key="distribution" value="AUTO"/>
<parameter key="early_stopping" value="false"/>
<parameter key="stopping_rounds" value="1"/>
<parameter key="stopping_metric" value="AUTO"/>
<parameter key="stopping_tolerance" value="0.001"/>
<parameter key="max_runtime_seconds" value="0"/>
<list key="expert_parameters"/>
</operator>
<operator activated="false" class="concurrency:parallel_decision_tree" compatibility="9.6.000" expanded="true" height="103" name="Decision Tree (2)" width="90" x="45" y="340">
<parameter key="criterion" value="information_gain"/>
<parameter key="maximal_depth" value="10"/>
<parameter key="apply_pruning" value="true"/>
<parameter key="confidence" value="0.1"/>
<parameter key="apply_prepruning" value="true"/>
<parameter key="minimal_gain" value="0.01"/>
<parameter key="minimal_leaf_size" value="2"/>
<parameter key="minimal_size_for_split" value="4"/>
<parameter key="number_of_prepruning_alternatives" value="3"/>
</operator>
<operator activated="false" class="k_nn" compatibility="9.6.000" expanded="true" height="82" name="k-NN (2)" width="90" x="179" y="340">
<parameter key="k" value="5"/>
<parameter key="weighted_vote" value="true"/>
<parameter key="measure_types" value="MixedMeasures"/>
<parameter key="mixed_measure" value="MixedEuclideanDistance"/>
<parameter key="nominal_measure" value="NominalDistance"/>
<parameter key="numerical_measure" value="EuclideanDistance"/>
<parameter key="divergence" value="GeneralizedIDivergence"/>
<parameter key="kernel_type" value="radial"/>
<parameter key="kernel_gamma" value="1.0"/>
<parameter key="kernel_sigma1" value="1.0"/>
<parameter key="kernel_sigma2" value="0.0"/>
<parameter key="kernel_sigma3" value="2.0"/>
<parameter key="kernel_degree" value="3.0"/>
<parameter key="kernel_shift" value="1.0"/>
<parameter key="kernel_a" value="1.0"/>
<parameter key="kernel_b" value="0.0"/>
</operator>
<connect from_port="training set" to_op="Gradient Boosted Trees (2)" to_port="training set"/>
<connect from_op="Gradient Boosted Trees (2)" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.6.000" expanded="true" height="82" name="Apply Model (3)" width="90" x="45" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="performance_binominal_classification" compatibility="9.6.000" expanded="true" height="82" name="Performance (2)" width="90" x="179" y="34">
<parameter key="manually_set_positive_class" value="false"/>
<parameter key="main_criterion" value="first"/>
<parameter key="accuracy" value="true"/>
<parameter key="classification_error" value="false"/>
<parameter key="kappa" value="true"/>
<parameter key="AUC (optimistic)" value="false"/>
<parameter key="AUC" value="true"/>
<parameter key="AUC (pessimistic)" value="false"/>
<parameter key="precision" value="false"/>
<parameter key="recall" value="false"/>
<parameter key="lift" value="false"/>
<parameter key="fallout" value="false"/>
<parameter key="f_measure" value="false"/>
<parameter key="false_positive" value="false"/>
<parameter key="false_negative" value="false"/>
<parameter key="true_positive" value="false"/>
<parameter key="true_negative" value="false"/>
<parameter key="sensitivity" value="false"/>
<parameter key="specificity" value="false"/>
<parameter key="youden" value="false"/>
<parameter key="positive_predictive_value" value="false"/>
<parameter key="negative_predictive_value" value="false"/>
<parameter key="psep" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
</operator>
<connect from_port="model" to_op="Apply Model (3)" to_port="model"/>
<connect from_port="test set" to_op="Apply Model (3)" to_port="unlabelled data"/>
<connect from_op="Apply Model (3)" from_port="labelled data" to_op="Performance (2)" to_port="labelled data"/>
<connect from_op="Performance (2)" from_port="performance" to_port="performance 1"/>
<connect from_op="Performance (2)" from_port="example set" to_port="test set results"/>
<portSpacing port="source_model" spacing="0"/>
<portSpacing port="source_test set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_test set results" spacing="0"/>
<portSpacing port="sink_performance 1" spacing="0"/>
<portSpacing port="sink_performance 2" spacing="0"/>
</process>
</operator>
<connect from_op="Retrieve AirBnB Full" from_port="output" to_op="Filter Examples" to_port="example set input"/>
<connect from_op="Filter Examples" from_port="example set output" to_op="Discretize" to_port="example set input"/>
<connect from_op="Discretize" from_port="example set output" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="SMOTE Upsampling" to_port="exa"/>
<connect from_op="SMOTE Upsampling" from_port="ups" to_op="Select Attributes" to_port="example set input"/>
<connect from_op="Select Attributes" from_port="example set output" to_op="Weight by Information Gain" to_port="example set"/>
<connect from_op="Weight by Information Gain" from_port="weights" to_op="Select by Weights" to_port="weights"/>
<connect from_op="Weight by Information Gain" from_port="example set" to_op="Select by Weights" to_port="example set input"/>
<connect from_op="Select by Weights" from_port="example set output" to_op="Sample (Stratified)" to_port="example set input"/>
<connect from_op="Select by Weights" from_port="weights" to_port="result 2"/>
<connect from_op="Sample (Stratified)" from_port="example set output" to_op="Cross Validation (2)" to_port="example set"/>
<connect from_op="Cross Validation (2)" from_port="model" to_port="result 1"/>
<connect from_op="Cross Validation (2)" from_port="test result set" to_port="result 3"/>
<connect from_op="Cross Validation (2)" from_port="performance 1" to_port="result 4"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
<portSpacing port="sink_result 3" spacing="0"/>
<portSpacing port="sink_result 4" spacing="0"/>
<portSpacing port="sink_result 5" spacing="0"/>
</process>
</operator>
</process>