我正在尝试使用lightbgm中的lightbgm CV方法解决多分类问题
import lightgbm as lgb
dftrainLGB = lgb.Dataset(data = X_train,label = y_train)
params = {'objective': 'multiclass','num_class' : 3,'random_state': 42}
cv_results = lgb.cv(
params,dftrainLGB,num_boost_round=100,nfold=10,metrics='multi_logloss',early_stopping_rounds=10,verbose_eval=20
)
如何使用cv_results中的最佳参数来训练我的模型?确实:
model = lgb.train(params,dftrainLGB)
将不使用cv_results