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岭回归正则化：数据科学中的一个重要概念。

Ridge Regularization: An Essential Concept in Data Science.

作者信息

Hastie Trevor

机构信息

Department of Statistics, Department of Biomedical Data Science, Stanford University, Stanford, CA.

出版信息

Technometrics. 2020;62(4):426-433. doi: 10.1080/00401706.2020.1791959. Epub 2020 Aug 10.

DOI:10.1080/00401706.2020.1791959
PMID:36033922
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9410599/
Abstract

Ridge or more formally regularization shows up in many areas of statistics and machine learning. It is one of those essential devices that any good data scientist needs to master for their craft. In this brief , I have collected together some of the magic and beauty of ridge that my colleagues and I have encountered over the past 40 years in applied statistics.

摘要

岭回归，或者更正式地说正则化，在统计学和机器学习的许多领域都有出现。它是任何优秀的数据科学家在其专业领域都需要掌握的重要工具之一。在本简报中，我汇集了过去40年里我和同事们在应用统计学中所遇到的岭回归的一些奇妙之处和魅力所在。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/161126a47bf7/nihms-1830542-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/6a2c3f37ddbc/nihms-1830542-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/49d29f16da96/nihms-1830542-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/94b172ba6686/nihms-1830542-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/6c684b017a46/nihms-1830542-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/161126a47bf7/nihms-1830542-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/6a2c3f37ddbc/nihms-1830542-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/49d29f16da96/nihms-1830542-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/94b172ba6686/nihms-1830542-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/6c684b017a46/nihms-1830542-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11d6/9410599/161126a47bf7/nihms-1830542-f0005.jpg

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