notebooks/example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "09b71c74-e492-4902-b65d-ed67cf353eb6",
   "metadata": {},
   "source": [
    "This notebook shows an example how this package can be used to perform feature reduction on the **Boston Housing** dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b2a06ec-ca4c-4974-b64b-c23d3dfb819a",
   "metadata": {},
   "source": [
    "### Import necessary packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e52bb669-ab25-4bce-ac40-69850dc8ef5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from multicollinearity.feature_reduction import MultiCollinearity"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a356f28-87db-4b8c-9e5b-2c05bb416497",
   "metadata": {},
   "source": [
    "### Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e7eef6d7-78f9-4e40-baac-ad32ec1cb930",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(506, 14)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../data/HousingData.csv.gz')\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0f2f3061-a1f3-44c8-b868-7833fd911494",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CRIM</th>\n",
       "      <th>ZN</th>\n",
       "      <th>INDUS</th>\n",
       "      <th>CHAS</th>\n",
       "      <th>NOX</th>\n",
       "      <th>RM</th>\n",
       "      <th>AGE</th>\n",
       "      <th>DIS</th>\n",
       "      <th>RAD</th>\n",
       "      <th>TAX</th>\n",
       "      <th>PTRATIO</th>\n",
       "      <th>B</th>\n",
       "      <th>LSTAT</th>\n",
       "      <th>MEDV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00632</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.538</td>\n",
       "      <td>6.575</td>\n",
       "      <td>65.2</td>\n",
       "      <td>4.0900</td>\n",
       "      <td>1</td>\n",
       "      <td>296</td>\n",
       "      <td>15.3</td>\n",
       "      <td>396.90</td>\n",
       "      <td>4.98</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.02731</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>6.421</td>\n",
       "      <td>78.9</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>242</td>\n",
       "      <td>17.8</td>\n",
       "      <td>396.90</td>\n",
       "      <td>9.14</td>\n",
       "      <td>21.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02729</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.469</td>\n",
       "      <td>7.185</td>\n",
       "      <td>61.1</td>\n",
       "      <td>4.9671</td>\n",
       "      <td>2</td>\n",
       "      <td>242</td>\n",
       "      <td>17.8</td>\n",
       "      <td>392.83</td>\n",
       "      <td>4.03</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>6.998</td>\n",
       "      <td>45.8</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18.7</td>\n",
       "      <td>394.63</td>\n",
       "      <td>2.94</td>\n",
       "      <td>33.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.06905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.458</td>\n",
       "      <td>7.147</td>\n",
       "      <td>54.2</td>\n",
       "      <td>6.0622</td>\n",
       "      <td>3</td>\n",
       "      <td>222</td>\n",
       "      <td>18.7</td>\n",
       "      <td>396.90</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      CRIM    ZN  INDUS  CHAS    NOX     RM   AGE     DIS  RAD  TAX  PTRATIO  \\\n",
       "0  0.00632  18.0   2.31   0.0  0.538  6.575  65.2  4.0900    1  296     15.3   \n",
       "1  0.02731   0.0   7.07   0.0  0.469  6.421  78.9  4.9671    2  242     17.8   \n",
       "2  0.02729   0.0   7.07   0.0  0.469  7.185  61.1  4.9671    2  242     17.8   \n",
       "3  0.03237   0.0   2.18   0.0  0.458  6.998  45.8  6.0622    3  222     18.7   \n",
       "4  0.06905   0.0   2.18   0.0  0.458  7.147  54.2  6.0622    3  222     18.7   \n",
       "\n",
       "        B  LSTAT  MEDV  \n",
       "0  396.90   4.98  24.0  \n",
       "1  396.90   9.14  21.6  \n",
       "2  392.83   4.03  34.7  \n",
       "3  394.63   2.94  33.4  \n",
       "4  396.90    NaN  36.2  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a04d680-6f47-4003-b0c9-0908b468675b",
   "metadata": {},
   "source": [
    "Let's assume that MEDV is the target variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aa88e631-d03e-45da-9002-ea11b8f57c2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "target = 'MEDV'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94a4fd3b-8278-4896-a550-096addc6d9c3",
   "metadata": {},
   "source": [
    "Now this particular dataset doesn't have huge multicollinearity issue, so let's introduce a little anarchy, I mean... multicollinearity, in this data. We will add an extraneous feature called `EXTRA`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8fe2895a-b5a3-40bf-ad96-05174d50572e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['EXTRA'] = (.01 * df['RAD']) + (.02 * df['ZN']) - (.003 * df['CRIM']) + np.random.uniform()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88fc51cb-36ff-43fc-bf66-5408c7edcd0f",
   "metadata": {},
   "source": [
    "### **Step 1:** Initialize the `Multicollinearity` class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8ea97a9e-8c86-469b-8df3-097b0e0213c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "mc = MultiCollinearity(df, target, corr_plot=True, verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9560be25-5e21-42dd-9a3a-cc5c195be1f5",
   "metadata": {},
   "source": [
    "### **Step 2:** Perform feature reduction based on the pairwise correlations. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de77c6b3-d167-4310-9024-dfb9cdd68203",
   "metadata": {},
   "source": [
    "Although it's not necessary, we can reduce some features based on pairwise correlations before running the multi-collinearity-based feature reduction step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5f3cd2f4-3d31-40b8-bbf0-08b6162c9d69",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Discarded 0 rows with missing values\n",
      "INFO: Discarded 0 columns with constant values\n",
      "INFO: Discarded 0 categorical columns\n",
      "INFO: Input number of features: 14\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DROP: EXTRA\t[Highly correlated with ZN (0.99)]\n",
      "DROP: RAD\t[Highly correlated with TAX (0.90)]\n",
      "STOP: The max pairwise correlation (0.77) is below threshold (0.80)\n"
     ]
    }
   ],
   "source": [
    "df_temp = mc.pairwise_corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1632a9b-76a6-4a61-aedc-ac2a30453e31",
   "metadata": {},
   "source": [
    "The pairwise correlation based feature reduction step removed two features."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94aa365f-984c-4e0f-a50a-b4f70b77e66d",
   "metadata": {},
   "source": [
    "### **Step 3:** The final feature reduction step, using multi-collinearity."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29cfa08b-3620-4022-9197-5788aeeca0b2",
   "metadata": {},
   "source": [
    "Please note that for demonstration purposes ONLY, we will use a very low value for the condition index threshold. (The default value is 30.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4099fa68-1478-45de-9b39-2bf3a44c28d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DROP: TAX [It leans the most on the eigen vector with the lowest eigen value (0.16)]\n",
      "DROP: ZN [It leans the most on the eigen vector with the lowest eigen value (0.18)]\n",
      "DROP: AGE [It leans the most on the eigen vector with the lowest eigen value (0.18)]\n",
      "DROP: RM [It leans the most on the eigen vector with the lowest eigen value (0.19)]\n",
      "DROP: NOX [It leans the most on the eigen vector with the lowest eigen value (0.19)]\n",
      "STOP: The condition index (3.35) is below threshold (4.00)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_slim = mc.multi_collin(cond_index_tol=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "56008797-7049-4954-b472-9d8ba12b9a95",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_slim.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d29749d-620b-4424-ab2e-656ed6869349",
   "metadata": {},
   "source": [
    "After the two steps of feature reduction process, we have 8 features left."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}