lime.py

import lime
import lime.lime_tabular

explainer = lime.lime_tabular.LimeTabularExplainer(X_train.values,
                                                   mode = 'regression',
                                                   feature_names = X_train.columns,
                                                   categorical_features = [3], 
                                                   categorical_names = ['CHAS'], 
                                                   discretize_continuous = True)
                                                   
np.random.seed(42)
exp = explainer.explain_instance(X_train.values[31], rf.predict, num_features = 5)
exp.show_in_notebook(show_all=False) #only the features used in the explanation are displayed

exp = explainer.explain_instance(X_train.values[85], rf.predict, num_features = 5)
exp.show_in_notebook(show_all=False)