RandomForest.py 文件源码

def model_extra_trees_regression(Xtrain,Xtest,ytrain):

    X_train = Xtrain
    y_train = ytrain

    etr = ExtraTreesRegressor(n_jobs=1, random_state=0)
    param_grid = {}#'n_estimators': [500], 'max_features': [10,15,20]}
    model = GridSearchCV(estimator=etr, param_grid=param_grid, n_jobs=1, cv=10, scoring=RMSE)
    model.fit(X_train, y_train)
    print('Extra trees regression...')
    print('Best Params:')
    print(model.best_params_)
    print('Best CV Score:')
    print(-model.best_score_)

    y_pred = model.predict(Xtest)
    return y_pred, -model.best_score_


# read data, build model and do prediction
# read train data