run_model_fit.py 文件源码

def unscaled_pipelines():
    # Random forest parameters
    random_forest_kwargs = {
        'n_estimators': 10,
        'criterion': 'mse',
        'random_state': _RANDOM_STATE,
        'n_jobs': cpu_count(),
        'verbose': True,
    }
    # Gradient boosting parameters
    gradient_boost_kwargs = {
        'random_state': _RANDOM_STATE,
        'verbose': 1,
    }
    models = [
        DecisionTreeRegressor(max_depth=3, random_state=_RANDOM_STATE),
        # RandomForestRegressor(**random_forest_kwargs),
        # GradientBoostingRegressor(**gradient_boost_kwargs),
    ]
    pipelines = []
    for m in models:
        # Steps
        pipelines.append(make_pipeline(m))
    return pipelines