Generalized Principal Component Analysis

Generalized Principal Component Analysis

Rene Vidal , Yi Ma , Shankar Sastry
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Apr 11, 2016 · 英語 · キンドル (598 ページ)
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本の詳細

形式 キンドル
ページ数 598
言語 英語
公開されました Apr 11, 2016
出版社 Springer
ISBN-10 0387878114
ISBN-13 9780387878119

説明

This work lays the groundwork for understanding generalized principal component analysis (GPCA), a cutting-edge method in statistical analysis. The authors, recognized experts in their fields, delve into the mathematical foundations that underpin GPCA, offering insights into its applications and implications in various domains. By weaving together theory and practical examples, they provide readers with a solid framework to grasp the complexities of high-dimensional data.

Readers are guided through the latest advancements in this evolving field, encouraging exploration beyond traditional methods. The book serves not only as a resource for students and researchers but also as a critical reference for professionals seeking to leverage GPCA in real-world scenarios, promoting innovative approaches to data analysis.

ジャンル

科学&技術
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