Statistical foundation of data science

著者
    • Fan, Jianqing
    • Li, Runze
    • Zhang, Cun-Hui
    • Zou, Hui
    • Moraga, Paula
書誌事項

Statistical foundation of data science

by Jianqing Fan ... [et al.]

(A Chapman & Hall book)(Chapman & Hall/CRC data science series)

CRC Press, an imprint of Taylor & Francis Group, 2020

  • : hbk.

この図書・雑誌をさがす
注記

Other authors: Runze Li, Cun-Hui Zhang, Hui Zou, Paula Moraga

Includes bibliographical references (p. 683-729) and index

内容説明・目次

内容説明

Provides theoretical insights and justification of the statistical procedures for the analysis of high-dimensional data Presents a general framework of regularization methods Covers feature screening for ultrahigh-dimensional data Describes large-scale covariance estimation

目次

1. Introduction. 2. Multiple and Nonparametric Regression. 3. Introduction to Penalized Least-Squares. 4. Penalized Least Squares: Properties. 5. Generalized Linear Models and Penalized Likelihood. 6. Penalized M-estimators. 7. High Dimensional Inference 8. Feature Screening. 9. Covariance Regularization and Graphical Models. 10. Covariance Learning and Factor Models. 11. Applications of Factor Models and PCA. 12. Supervised Learning. 13. Unsupervised Learning. 14. An Introduction to Deep Learning.

「Nielsen BookData」 より

関連文献: 2件中  1-2を表示
詳細情報
ページトップへ