江湖骗子
发表于 2025-3-28 15:08:51
Bagging,nts, measures of it, residuals, classifications and others. Ensemble methods make many passes through the data after which the results are combined. One immediate benefit can be estimates with better out-of-sample performance. The statistical learning procedure called “bagging” is where we start.
FORGO
发表于 2025-3-28 20:48:39
Boosting,ore flexible. A much wider range of response variables types are can be used, all within the same basic algorithmic structure. Just as for random forests, there are several useful ways to study the output, and excellent software exists within R.
定点
发表于 2025-3-29 01:08:52
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sterilization
发表于 2025-3-29 03:28:23
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总
发表于 2025-3-29 09:51:48
978-3-319-82969-2Springer Nature Switzerland AG 2016
模范
发表于 2025-3-29 11:35:21
Statistical Learning from a Regression Perspective978-3-319-44048-4Series ISSN 1431-875X Series E-ISSN 2197-4136
都相信我的话
发表于 2025-3-29 16:52:13
Random Forests,In the last chapter some of the weaknesses of bagging were discussed. In this chapter, random forests is introduced in part to address these weaknesses. Random forests is a legitimate and very useful statistical learning procedure that can be successfully used in practice.
MUT
发表于 2025-3-29 23:48:16
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