Random Forests
Random Forests
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DOI：
10.1007/978-1-4419-9326-7_5
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发表时间：
2012-01-01
期刊：
影响因子：
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通讯作者：
Stevens, John R.
中科院分区：
文献类型：
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作者：
Cutler, Adele;Cutler, D. Richard;Stevens, John R.
随机森林由Leo Breiman [6]引入，他受到Amit和Geman [2]早期工作的启发。虽然从[6]的描述中并不明显，但随机森林是Breiman装袋思想的扩展[5]，并且是作为Boosting的竞争对手而开发的。随机森林可用于分类响应变量（在[6]中称为“分类”）或连续响应（称为“回归”）。类似地，预测变量可以是分类的或连续的。
Random Forests were introduced by Leo Breiman [6] who was inspired by earlier work by Amit and Geman [2]. Although not obvious from the description in [6], Random Forests are an extension of Breiman’s bagging idea [5] and were developed as a competitor to boosting. Random Forests can be used for either a categorical response variable, referred to in [6] as “classification,” or a continuous response, referred to as “regression.” Similarly, the predictor variables can be either categorical or continuous.