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Titlebook: Statistical Learning from a Regression Perspective; Richard A. Berk Textbook 20162nd edition Springer Nature Switzerland AG 2016 classific

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樓主: Grievous
31#
發(fā)表于 2025-3-26 23:37:51 | 只看該作者
Classification and Regression Trees (CART),Regression Trees (CART) is emphasized. Tree structures are less important as stand-alone data analysis procedures than in the past. But they are essential components of many very effective statistical learning procedures discussed in later chapters. They also raise important conceptual and technical
32#
發(fā)表于 2025-3-27 04:59:10 | 只看該作者
33#
發(fā)表于 2025-3-27 05:23:53 | 只看該作者
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.
34#
發(fā)表于 2025-3-27 12:39:20 | 只看該作者
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發(fā)表于 2025-3-27 13:47:48 | 只看該作者
36#
發(fā)表于 2025-3-27 18:30:33 | 只看該作者
Textbook 20162nd editionof predictors, and when it is important to characterize how the predictors are related to the response.?.This fully revised new edition includes important developments over the past 8 years. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis derives
37#
發(fā)表于 2025-3-28 01:00:37 | 只看該作者
38#
發(fā)表于 2025-3-28 06:10:27 | 只看該作者
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發(fā)表于 2025-3-28 06:47:35 | 只看該作者
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發(fā)表于 2025-3-28 13:36:49 | 只看該作者
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