I am building a standard RandomForest classifier (named model, see the code below) using scikit-learn package. Now, I want to get all parameters of one Randomforest classifier (including its trees (estimators)), so that I can manually draw the flow chart for each tree of the RandomForest classifier. I wonder if anyone knows how it can be done?
Thank you in advance.
#Import Library from sklearn.ensemble import RandomForestClassifier #use RandomForestRegressor for regression problem #Assumed you have, X (predictor) and Y (target) for training data set and x_test(predictor) of test_dataset # Create Random Forest object model= RandomForestClassifier(n_estimators=10, max_depth=5) #n_estimators=1000 oob_score = True #==== #X, y = input_X, input_y from sklearn.cross_validation import train_test_split X_train, X_test, y_train, y_test = train_test_split(X,y,test_size = 0.2, random_state = 4) # Train the model using the training sets and check score model.fit(X_train, y_train) #Predict Output y_pred_train = model.predict(X_train) y_pred_test = model.predict(X_test) #accuracy from sklearn.metrics import accuracy_score print(accuracy_score(y_train,y_pred_train)) print(accuracy_score(y_test,y_pred_test))