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简介
Analysis of Multivariate and High-Dimensional Data 豆 0.0分
资源最后更新于 2020-09-05 22:04:51
作者：Koch, Inge
出版社：Cambridge University Press
出版日期：2013-01
ISBN：9780521887939
文件格式： pdf
标签： textbook統計 统计学 @網
简介· · · · · ·
“Big data” poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world – integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guar...
目录
Part I. Classical Methods:
1. Multidimensional data
2. Principal component analysis
3. Canonical correlation analysis
4. Discriminant analysis
Part II. Factors and Groupings:
5. Norms, proximities, features, and dualities
6. Cluster analysis
7. Factor analysis
8. Multidimensional scaling
Part III. Non-Gaussian Analysis:
9. Towards non-Gaussianity
10. Independent component analysis
11. Projection pursuit
12. Kernel and more independent component methods
13. Feature selection and principal component analysis revisited
Index.
1. Multidimensional data
2. Principal component analysis
3. Canonical correlation analysis
4. Discriminant analysis
Part II. Factors and Groupings:
5. Norms, proximities, features, and dualities
6. Cluster analysis
7. Factor analysis
8. Multidimensional scaling
Part III. Non-Gaussian Analysis:
9. Towards non-Gaussianity
10. Independent component analysis
11. Projection pursuit
12. Kernel and more independent component methods
13. Feature selection and principal component analysis revisited
Index.
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