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lightgbm-doc-zh's Introduction

LightGBM 中文文档

LightGBM 是一个梯度 boosting 框架, 使用基于学习算法的决策树. 它是分布式的, 高效的, 装逼的, 它具有以下优势:

  • 速度和内存使用的优化
    • 减少分割增益的计算量
    • 通过直方图的相减来进行进一步的加速
    • 减少内存的使用 减少并行学习的通信代价
  • 稀疏优化
  • 准确率的优化
    • Leaf-wise (Best-first) 的决策树生长策略
    • 类别特征值的最优分割
  • 网络通信的优化
  • 并行学习的优化
    • 特征并行
    • 数据并行
    • 投票并行
  • GPU 支持可处理大规模数据

更多有关 LightGBM 特性的详情, 请参阅: LightGBM 特性.

文档地址

项目负责人

项目贡献者

贡献指南

为了使项目更加便于维护，我们将文档格式全部转换成了 Markdown，同时更换了页面生成器。后续维护工作将完全在 Markdown 上进行。

小部分格式仍然存在问题，主要是链接和表格。需要大家帮忙找到，并提 PullRequest 来修复。

建议反馈

组织学习交流群

机器学习交流群: 629470233 （2000人）

大数据交流群: 214293307 （2000人）

了解我们: http://www.apachecn.org/organization/209.html

加入组织: http://www.apachecn.org/organization/209.html

更多信息请参阅: http://www.apachecn.org/organization/348.html

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