I am working on a binary classification using random forest model, neural networks in which am using SHAP to explain the model predictions. I followed the tutorial and wrote the below code to get the waterfall plot shown below row_to_show = 20 data_for_prediction = ord_test_t.iloc[row_to_show] # use 1 row of data here. Could use multiple rows if desired data_for_prediction_array = data_for_prediction.values.reshape(1, -1) rf_boruta.predict_proba(data_for_prediction_array) explainer = shap.TreeExplainer(rf_boruta) # Calculate Shap values shap_values = explainer.shap_values(data_for_prediction) shap.plots._waterfall.waterfall_legacy(explainer.expected_value[0], shap_values[0],ord_test_t.iloc[row_to_show]) This generated the plot as shown below However, I want to export this to dataframe and how can I do it? I expect my output to be like as shown below. I want to export this for the full dataframe. Can you help me please? Continue reading...
