机器学习算法决策树随机森林实践的相关内容

[帮助文档] 机器学习线性支持向量机算法组件的配置及示例

支持向量机SVM（Support Vector Machine）是基于统计学习理论的一种机器学习方法，通过寻求结构风险最小化，提高学习机泛化能力，从而实现经验风险和置信范围最小化。本文介绍线性支持向量机算法组件的配置方法及使用示例。

【机器学习算法】13、决策树与随机森林（非常的全面讲解和实践）（三）

5.SKLearn实践（部分）5.1.决策树之iris分类分类结果5.2.决策树对鸢尾花数据的两特征组合的分类分类结果：5.3.树回归回归结果：5.4.多输出的树回归回归结果：5.5.iris之随机森林分类分类结果：

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【机器学习算法】13、决策树与随机森林（非常的全面讲解和实践）（二）

3.算法流程3.1、ID3算法3.1.1、思想从信息论的知识中可以知道，期望信息越小，信息熵越大，从而样本纯度越低。ID3算法的核心思想就是以信息增益来度量特征选择，选择信息增益最大的特征进行分裂。算法采用自顶向下的贪婪搜索遍历可能的决策树空间（C4....

【机器学习算法】13、决策树与随机森林（非常的全面讲解和实践）（一）

1.简介决策树（Decision Tree）是一种非参数的有监督学习方法，它能够从一系列有特征和标签的数据中总结出决策规则，并用树状图的结构来呈现这些规则，以解决分类和回归问题。决策树算法容易理解，适用各种数据，在解决各种问题时都有良好表现，尤其是以树模型为核心的各种集成算...

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