lgbm回归参数解释

version：python 3.6
环境：anaconda/JupyterLab 0.27.0
操作系统：Windows 10

最近LightGBM模型运用比较多，打算整理一下各种参数：

from lightgbm.sklearn import LGBMRegressor
lgb_model = LGBMRegressor( 
    boosting_type='gbdt', 
    num_leaves=30, 
    max_depth=79, 
    learning_rate=0.1, 
    n_estimators=100, 
    max_bin=255, 
    subsample_for_bin=50000, 
    objective='regression', 
    min_split_gain=0, 
    min_child_weight=5, 
    min_child_samples=10, 
    subsample=1, 
    subsample_freq=1, 
    colsample_bytree=1, 
    reg_alpha=0, 
    reg_lambda=0, 
    seed=0, 
    nthread=-1, 
    silent=True, 
    huber_delta=1.0, 
    gaussian_eta=1.0, 
    fair_c=1.0, 
    poisson_max_delta_step=0.7, 
    drop_rate=0.1, 
    skip_drop=0.5, 
    max_drop=50, 
    uniform_drop=False, 
    xgboost_dart_mode=False,
    verbose_eval=100
)

翻译自https://github.com/Microsoft/LightGBM/blob/master/docs/Parameters.rst