I trained a prediction model with Scikit Learn in Python (Random Forest Regressor) and I want to extract somehow the weights of each feature to create an excel tool for manual prediction.
The only thing that I found is the
model.feature_importances_ but it doesn't help.
Is there any way to achieve it?
def performRandomForest(X_train, y_train, X_test, y_test): '''Perform Random Forest Regression''' from sklearn.ensemble import RandomForestRegressor model = RandomForestRegressor() model.fit( X_train , y_train ) #make predictions expected = y_test predicted = model.predict( X_test ) #summarize the fit of the model mse = np.mean(( predicted - expected )** 2) accuracy = ( model.score ( X_train , y_train )) return model, mse, accuracy
At the moment, I use the
model.predict([features]) to do it, but I need it in an excel file.