相关疑难解决方法(0)

我想用lgb.Dataset对LightGBM模型进行交叉验证,并使用early_stopping_rounds.以下方法在XGBoost的xgboost.cv中没有问题.我不想将Scikit Learn的方法与GridSearchCV一起使用,因为它不支持提前停止或lgb.Dataset.

import lightgbm as lgb
from sklearn.metrics import mean_absolute_error
dftrainLGB = lgb.Dataset(data = dftrain, label = ytrain, feature_name = list(dftrain))

params = {'objective': 'regression'}

cv_results = lgb.cv(
        params,
        dftrainLGB,
        num_boost_round=100,
        nfold=3,
        metrics='mae',
        early_stopping_rounds=10
        )

任务是进行回归,但以下代码会引发错误: Supported target types are: ('binary', 'multiclass'). Got 'continuous' instead.

LightGBM支持回归,还是我提供了错误的参数？