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Nov 5, 2024
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Created using Colab #38

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126 changes: 126 additions & 0 deletions lime_intro.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"authorship_tag": "ABX9TyMMXaToAGLsMRMF3TPy274u",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/mishelks/BizRecProject/blob/dev/lime_intro.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "aBo23Oai58-f",
"outputId": "0b47140e-6181-49ea-9635-0c80a6ca623b"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting lime\n",
" Downloading lime-0.2.0.1.tar.gz (275 kB)\n",
"\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/275.7 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m275.7/275.7 kB\u001b[0m \u001b[31m10.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
"Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from lime) (3.8.0)\n",
"Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from lime) (1.26.4)\n",
"Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from lime) (1.13.1)\n",
"Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from lime) (4.66.6)\n",
"Requirement already satisfied: scikit-learn>=0.18 in /usr/local/lib/python3.10/dist-packages (from lime) (1.5.2)\n",
"Requirement already satisfied: scikit-image>=0.12 in /usr/local/lib/python3.10/dist-packages (from lime) (0.24.0)\n",
"Requirement already satisfied: networkx>=2.8 in /usr/local/lib/python3.10/dist-packages (from scikit-image>=0.12->lime) (3.4.2)\n",
"Requirement already satisfied: pillow>=9.1 in /usr/local/lib/python3.10/dist-packages (from scikit-image>=0.12->lime) (10.4.0)\n",
"Requirement already satisfied: imageio>=2.33 in /usr/local/lib/python3.10/dist-packages (from scikit-image>=0.12->lime) (2.36.0)\n",
"Requirement already satisfied: tifffile>=2022.8.12 in /usr/local/lib/python3.10/dist-packages (from scikit-image>=0.12->lime) (2024.9.20)\n",
"Requirement already satisfied: packaging>=21 in /usr/local/lib/python3.10/dist-packages (from scikit-image>=0.12->lime) (24.1)\n",
"Requirement already satisfied: lazy-loader>=0.4 in /usr/local/lib/python3.10/dist-packages (from scikit-image>=0.12->lime) (0.4)\n",
"Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.18->lime) (1.4.2)\n",
"Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.18->lime) (3.5.0)\n",
"Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->lime) (1.3.0)\n",
"Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->lime) (0.12.1)\n",
"Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->lime) (4.54.1)\n",
"Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->lime) (1.4.7)\n",
"Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->lime) (3.2.0)\n",
"Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib->lime) (2.8.2)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib->lime) (1.16.0)\n",
"Building wheels for collected packages: lime\n",
" Building wheel for lime (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for lime: filename=lime-0.2.0.1-py3-none-any.whl size=283834 sha256=b515d66069bac0a1158b6deb11ab86d9339f6b016d519094703a56f0f62b4246\n",
" Stored in directory: /root/.cache/pip/wheels/fd/a2/af/9ac0a1a85a27f314a06b39e1f492bee1547d52549a4606ed89\n",
"Successfully built lime\n",
"Installing collected packages: lime\n",
"Successfully installed lime-0.2.0.1\n"
]
}
],
"source": [
"pip install lime\n"
]
},
{
"cell_type": "code",
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.ensemble import RandomForestRegressor\n",
"from lime.lime_tabular import LimeTabularExplainer\n",
"\n",
"\n",
"# Split the data\n",
"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
"\n",
"# Train a Random Forest Regressor\n",
"rf = RandomForestRegressor(n_estimators=100, random_state=42)\n",
"rf.fit(X_train, y_train)\n",
"\n",
"# Select an instance to explain\n",
"instance = X_test.iloc[0].values.reshape(1, -1)\n",
"\n",
"# Set up LIME for tabular data\n",
"explainer = LimeTabularExplainer(\n",
" training_data=X_train.values,\n",
" feature_names=X.columns,\n",
" mode='regression'\n",
")\n",
"\n",
"# Generate explanation for the chosen instance\n",
"exp = explainer.explain_instance(\n",
" data_row=instance[0],\n",
" predict_fn=rf.predict\n",
")\n",
"\n",
"# Display the explanation\n",
"exp.show_in_notebook(show_table=True)\n"
],
"metadata": {
"id": "LVPfcEZI8oYd"
},
"execution_count": null,
"outputs": []
}
]
}