模型参数参数名参数描述可选值boosting_type模型提升方式‘gbdt’、‘dart’、‘goss’、‘rf’num_leaves每个基学习器的最大叶子默认31max_depth基学习器树的最大深度默认-1，没有限制learning_rateboosting学习率默认0.1n_estimators基学习器的数量默认10max_bin特征值的分桶数默认255subsample_for_bin....

文章 2023-01-17 来自：开发者社区

XGBoost Python API参考以及各参数意义

常规参数参数参数描述可选值booster使用哪种增压器，可以是gbtree, gblinar或dart。Gbtree和dart采用基于树的模型，而gblinear采用线性函数‘gbtree’、‘gblinar’、‘dart’，默认gbtreesilent是否打印运行信息0代表打印，1，默认0nthread用于运行xgboost的并行线程数默认最大数num_pbuffer预测缓冲区的大小，通常设置....

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更新时间 2024-10-17 18:05:58

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分布式计算框架 MaxCompute MaxFrame

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