lightgbm 各任务基本代码

lightgbm适用于多个任务(回归，二分类，多分类)，具体的参数需要做出变化，下面给出各任务的基本代码。

回归

import sklearn
from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.metrics import roc_auc_score,mean_squared_error
import numpy as np
import lightgbm as lgb

boston_price = datasets.load_boston()

data = boston_price.data
target = boston_price.target

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2)
print("Train data length:", len(X_train))
print("Test data length:", len(X_test))

# 转换为Dataset数据格式
lgb_train = lgb.Dataset(X_train, y_train)
lgb_eval = lgb.Dataset(X_test, y_test, reference=lgb_train)

# 参数
params = {
   
   
    'boosting_type': 'gbdt',  # 设置提升类型