diff --git a/xai/1_xai.ipynb b/xai/1_xai.ipynb new file mode 100644 index 0000000..de958f0 --- /dev/null +++ b/xai/1_xai.ipynb @@ -0,0 +1,37757 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "source": [ + "![](./images/EscUpmPolit_p.gif \"UPM\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "source": [ + "# Course Notes for Learning Intelligent Systems" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "source": [ + "Department of Telematic Engineering Systems, Universidad Politécnica de Madrid, © Carlos A. Iglesias" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "# Table of Contents\n", + "* [Objectives](#Objectives)\n", + "* [Installation](#Installation)\n", + "* [Interpretation with LIME](#Interpretation with LIME)\n", + "* [Interpretation with SHAP](#Interpretation with SHAP)\n", + " * [Force plot](#Force plot)\n", + " * [Mean SHAP](#Mean SHAP)\n", + " * [Beeswarm](#Beeswarm)\n", + "* [References](#References)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "slide" + } + }, + "source": [ + "# Objectives" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "subslide" + } + }, + "source": [ + "In this session we are going to learn how to interpret and explain machine learning models." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Load data" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# library for displaying plots\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# display plots in the notebook \n", + "%matplotlib inline\n", + "\n", + "## First, we repeat the load and preprocessing steps\n", + "\n", + "# Load data\n", + "from sklearn import datasets\n", + "iris = datasets.load_iris()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Train-test splitting and preprocessing\n", + "We don't normalize to see the explanations with 'raw data', but you can try when the data is normalized." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# Training and test spliting\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "x_iris, y_iris = iris.data, iris.target\n", + "\n", + "# Test set will be the 25% taken randomly\n", + "x_train, x_test, y_train, y_test = train_test_split(x_iris, y_iris, test_size=0.25, random_state=33)\n", + "\n", + "# Preprocess: normalize\n", + "#from sklearn import preprocessing\n", + "#SS = preprocessing.StandardScaler()\n", + "#scaler = SS.fit(x_train)\n", + "#x_train = scaler.transform(x_train)\n", + "#x_test = scaler.transform(x_test)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Train model" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy in training 0.9642857142857143\n", + "Accuracy in testing 0.9473684210526315\n", + " precision recall f1-score support\n", + "\n", + " setosa 1.00 1.00 1.00 8\n", + " versicolor 0.85 1.00 0.92 11\n", + " virginica 1.00 0.89 0.94 19\n", + "\n", + " accuracy 0.95 38\n", + " macro avg 0.95 0.96 0.95 38\n", + "weighted avg 0.96 0.95 0.95 38\n", + "\n" + ] + } + ], + "source": [ + "from sklearn.neighbors import KNeighborsClassifier\n", + "import numpy as np\n", + "\n", + "# Create kNN model\n", + "modelKNN = KNeighborsClassifier(n_neighbors=15)\n", + "\n", + "# Train the model using the training sets\n", + "modelKNN.fit(x_train, y_train) \n", + "\n", + "# Evaluate Accuracy in training\n", + "\n", + "from sklearn import metrics\n", + "y_train_pred = modelKNN.predict(x_train)\n", + "print(\"Accuracy in training\", metrics.accuracy_score(y_train, y_train_pred))\n", + "\n", + "# Now we evaluate error in testing\n", + "y_test_pred = modelKNN.predict(x_test)\n", + "print(\"Accuracy in testing \", metrics.accuracy_score(y_test, y_test_pred))\n", + "\n", + "#print metrics\n", + "print(metrics.classification_report(y_test, y_test_pred, target_names=iris.target_names))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Installation" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install -q shap umap-learn lime xgboost seaborn umap" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Interpretation with LIME\n", + "\n", + "Mirar https://coderzcolumn.com/tutorials/machine-learning/how-to-use-lime-to-understand-sklearn-models-predictions \n", + "\n", + "https://www.kaggle.com/code/joshuaswords/predicting-a-stroke-shap-lime-explainer-eli5/notebook" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "from lime.lime_tabular import LimeTabularExplainer\n", + "\n", + "lime_explainer = LimeTabularExplainer(\n", + " training_data=x_train,\n", + " feature_names=iris.feature_names,\n", + " class_names=iris.target_names,\n", + " mode=\"classification\",\n", + " discretize_continuous=True\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we'll pick a sample from the testing data that we want to explain:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']\n", + "[5.7 2.9 4.2 1.3]\n", + "['setosa' 'versicolor' 'virginica']\n", + "1\n" + ] + } + ], + "source": [ + "idx = 0 # index of the sample we want to explain\n", + "print(iris.feature_names)\n", + "print(x_test[idx])\n", + "print(iris.target_names)\n", + "print(y_test[idx])" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "exp = lime_explainer.explain_instance(x_test[idx], modelKNN.predict_proba)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we can print out the top three features that are contributing to the prediction:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4.00 < petal length (cm) <= 5.00: 0.53\n", + "1.25 < petal width (cm) <= 1.80: -0.06\n", + "5.65 < sepal length (cm) <= 6.33: 0.01\n" + ] + } + ], + "source": [ + "for i in range(3):\n", + " print(f\"{exp.as_list()[i][0]}: {exp.as_list()[i][1]:.2f}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This tells us that the most important feature for this prediction is petal width (cm), and that a value of 0.80 or less is strongly associated with the \"setosa\" class.\n", + "\n", + "We can also visualize the explanation using a bar chart:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from lime import lime_tabular\n", + "\n", + "fig = exp.as_pyplot_figure()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To start, we'll generate a of explanation for one instance in the testing dataset, next, we'll use these explanations to generate a decision plot:" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + "
\n", + " \n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "exp = lime_explainer.explain_instance(\n", + " data_row=x_test[1], \n", + " predict_fn=modelKNN.predict_proba\n", + ")\n", + "\n", + "from IPython.core.display import HTML\n", + "\n", + "#exp.show_in_notebook()\n", + "#exp.show_in_notebook(show_table=True) # Workaround Error with Display object\n", + "display(HTML(exp.as_html()))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Interpretation with SHAP" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "ExactExplainer explainer: 113it [00:12, 3.20it/s] " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(112, 4)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# Init SHAP\n", + "import shap\n", + "shap.initjs()\n", + "\n", + "# Get shap values\n", + "explainer = shap.Explainer(\n", + " modelKNN.predict, x_train, feature_names=iris.feature_names)\n", + "shap_values = explainer(x_train)\n", + "\n", + "print(np.shape(shap_values))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Force plot" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Waterfall plot for first observation\n", + "shap.plots.waterfall(shap_values[0])\n", + "\n", + "# Save figure\n", + "#utils.save_fig(\"MA5_waterfall_plot\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Mean SHAP" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Mean SHAP\n", + "shap.plots.bar(shap_values)\n", + "\n", + "# Save figure\n", + "#utils.save_fig(\"MA5_mean_shap\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Mean SHAP for one instance is very similary to force plot\n", + "shap.plots.bar(shap_values[0])\n", + "\n", + "# Save figure\n", + "#utils.save_fig(\"MA5_mean_shap\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Beeswarm" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Beeswarm plot\n", + "shap.plots.beeswarm(shap_values,show=False)\n", + "\n", + "# Save figure\n", + "#utils.save_fig(\"MA5_beewarm_plot\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "source": [ + "## References\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "source": [ + "* [Interpretability Revisited: LIME and SHAP in prose and code](https://colab.research.google.com/drive/1pjPzsw_uZew-Zcz646JTkRDhF2GkPk0N)\n", + "* [SHAP documentation](https://shap.readthedocs.io/)\n", + "* [LIME documentation](https://github.com/marcotcr/lime)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "source": [ + "## Licence" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "slideshow": { + "slide_type": "skip" + } + }, + "source": [ + "The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n", + "\n", + "© Carlos A. Iglesias, Universidad Politécnica de Madrid." + ] + } + ], + "metadata": { + "celltoolbar": "Slideshow", + "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": "3.12.2" + }, + "latex_envs": { + "LaTeX_envs_menu_present": true, + "autocomplete": true, + "bibliofile": "biblio.bib", + "cite_by": "apalike", + "current_citInitial": 1, + "eqLabelWithNumbers": true, + "eqNumInitial": 1, + "hotkeys": { + "equation": "Ctrl-E", + "itemize": "Ctrl-I" + }, + "labels_anchors": false, + "latex_user_defs": false, + "report_style_numbering": false, + "user_envs_cfg": false + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}