【799】lightGBM实现

参考：LightGBM使用

参考：在Python中使用Lightgbm

参考：官网 - lightgbm.LGBMClassifier

from sklearn.model_selection import train_test_split
 
X_train, X_test, y_train, y_test = train_test_split(stat_data, mode_data, test_size=0.2) 
 
import lightgbm as lgb 
from sklearn.metrics import mean_squared_error
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.datasets import  make_classification
 
gbm = lgb.LGBMRegressor(objective='regression',num_leaves=1024,learning_rate=0.05,n_estimators=512,max_depth=15)
gbm.fit(X_train, y_train,eval_set=[(X_test, y_test)],eval_metric='l1',early_stopping_rounds=5)
 
y_pred = gbm.predict(X_test, num_iteration=gbm.best_iteration_)