{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"test_sharp.ipynb","provenance":[],"collapsed_sections":[],"authorship_tag":"ABX9TyMWrNcnueB3TNm/XDAJSbu2"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Xe0Sh7jnv3Dg","executionInfo":{"status":"ok","timestamp":1607409462572,"user_tz":-480,"elapsed":3895,"user":{"displayName":"如子","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi3ItGjzEGzUOlXTUHjOgeuVA5TICdNcY-Q1TGicA=s64","userId":"01997730851420384589"}},"outputId":"9d00898f-f128-4d4b-8ab9-f3ddfb077b18"},"source":["!pip install shap"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Requirement already satisfied: shap in /usr/local/lib/python3.6/dist-packages (0.37.0)\n","Requirement already satisfied: numba in /usr/local/lib/python3.6/dist-packages (from shap) (0.48.0)\n","Requirement already satisfied: tqdm>4.25.0 in /usr/local/lib/python3.6/dist-packages (from shap) (4.41.1)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from shap) (1.18.5)\n","Requirement already satisfied: slicer==0.0.3 in /usr/local/lib/python3.6/dist-packages (from shap) (0.0.3)\n","Requirement already satisfied: pandas in /usr/local/lib/python3.6/dist-packages (from shap) (1.1.4)\n","Requirement already satisfied: scikit-learn in /usr/local/lib/python3.6/dist-packages (from shap) (0.22.2.post1)\n","Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from shap) (1.4.1)\n","Requirement already satisfied: llvmlite<0.32.0,>=0.31.0dev0 in /usr/local/lib/python3.6/dist-packages (from numba->shap) (0.31.0)\n","Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from numba->shap) (50.3.2)\n","Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.6/dist-packages (from pandas->shap) (2.8.1)\n","Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas->shap) (2018.9)\n","Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.6/dist-packages (from scikit-learn->shap) (0.17.0)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.7.3->pandas->shap) (1.15.0)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":43},"id":"oGqJ3A6KxAwE","executionInfo":{"status":"ok","timestamp":1607409463885,"user_tz":-480,"elapsed":4281,"user":{"displayName":"如子","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi3ItGjzEGzUOlXTUHjOgeuVA5TICdNcY-Q1TGicA=s64","userId":"01997730851420384589"}},"outputId":"9c623855-e52f-4b85-8ddc-41a717a29579"},"source":["from sklearn.feature_extraction.text import TfidfVectorizer\n","from sklearn.model_selection import train_test_split\n","from sklearn.linear_model import LogisticRegression\n","\n","import numpy as np\n","import shap\n","\n","shap.initjs()"],"execution_count":2,"outputs":[{"output_type":"display_data","data":{"text/html":["
"],"text/plain":[""]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"IcFmCcT2xE1c","executionInfo":{"status":"ok","timestamp":1607409470253,"user_tz":-480,"elapsed":6322,"user":{"displayName":"如子","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi3ItGjzEGzUOlXTUHjOgeuVA5TICdNcY-Q1TGicA=s64","userId":"01997730851420384589"}}},"source":["corpus, y = shap.datasets.imdb()\n","corpus_train, corpus_test, y_train, y_test = train_test_split(corpus, y, test_size=.2, random_state=7)\n","\n","vectorizer = TfidfVectorizer(binary=True)\n","X_train = vectorizer.fit_transform(corpus_train)\n","X_test = vectorizer.transform(corpus_test)"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"5S9p0n3-xG47","executionInfo":{"status":"ok","timestamp":1607409470857,"user_tz":-480,"elapsed":6891,"user":{"displayName":"如子","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi3ItGjzEGzUOlXTUHjOgeuVA5TICdNcY-Q1TGicA=s64","userId":"01997730851420384589"}},"outputId":"8dcada67-dd6b-4c36-eccf-946a8d5e6049"},"source":["model = LogisticRegression(C = .1)\n","model.fit(X_train, y_train)"],"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LogisticRegression(C=0.1, class_weight=None, dual=False, fit_intercept=True,\n"," intercept_scaling=1, l1_ratio=None, max_iter=100,\n"," multi_class='auto', n_jobs=None, penalty='l2',\n"," random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n"," warm_start=False)"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-SF7ZapuxJa_","executionInfo":{"status":"ok","timestamp":1607409475772,"user_tz":-480,"elapsed":10475,"user":{"displayName":"如子","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi3ItGjzEGzUOlXTUHjOgeuVA5TICdNcY-Q1TGicA=s64","userId":"01997730851420384589"}},"outputId":"98b1f045-ede8-44fe-a6f4-113ae55ec95f"},"source":["explainer = shap.LinearExplainer(model, X_train, feature_dependence='independent')\n","shap_values = explainer.shap_values(X_test)\n","# we need to pass a dense version for the plotting functions\n","X_test_array = X_test.toarray()"],"execution_count":5,"outputs":[{"output_type":"stream","text":["The option feature_dependence has been renamed to feature_perturbation!\n","The option feature_perturbation=\"independent\" is has been renamed to feature_perturbation=\"interventional\"!\n","The feature_perturbation option is now deprecated in favor of using the appropriate masker (maskers.Independent, or maskers.Impute)\n"],"name":"stderr"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":585},"id":"LMdmlwt2xOiK","executionInfo":{"status":"ok","timestamp":1607409478859,"user_tz":-480,"elapsed":11401,"user":{"displayName":"如子","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi3ItGjzEGzUOlXTUHjOgeuVA5TICdNcY-Q1TGicA=s64","userId":"01997730851420384589"}},"outputId":"a824f0a2-b516-42df-e5b1-2dba531de1a7"},"source":["shap.summary_plot(shap_values, X_test_array, feature_names=vectorizer.get_feature_names())"],"execution_count":6,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["
"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":265},"id":"KG-TQF0o_XA3","executionInfo":{"status":"ok","timestamp":1607409519700,"user_tz":-480,"elapsed":3326,"user":{"displayName":"如子","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi3ItGjzEGzUOlXTUHjOgeuVA5TICdNcY-Q1TGicA=s64","userId":"01997730851420384589"}},"outputId":"fc4777ad-b00b-44a6-f283-138ffe625598"},"source":["ind = 10\n","\n","print(\"Positive\" if y_test[ind] else \"Negative\", \"Review:\")\n","print(corpus_test[ind])\n","\n","shap.initjs()\n","shap.force_plot(\n"," explainer.expected_value, shap_values[ind,:], X_test_array[ind,:],\n"," feature_names=vectorizer.get_feature_names()\n",")"],"execution_count":7,"outputs":[{"output_type":"stream","text":["Positive Review:\n","I would never have thought I would almost cry viewing one minute excerpted from a 1920 black and white movie without sound. Thanks to Martin Scorsese I did (the movie was from F. Borzage). You will start to understand (if it's not already the case), what makes a good movie.\n","\n"],"name":"stdout"},{"output_type":"display_data","data":{"text/html":["
"],"text/plain":[""]},"metadata":{"tags":[]}},{"output_type":"execute_result","data":{"text/html":["\n","
\n","
\n"," Visualization omitted, Javascript library not loaded!
\n"," Have you run `initjs()` in this notebook? If this notebook was from another\n"," user you must also trust this notebook (File -> Trust notebook). If you are viewing\n"," this notebook on github the Javascript has been stripped for security. If you are using\n"," JupyterLab this error is because a JupyterLab extension has not yet been written.\n","
\n","