发帖
雷达卡
Author(s): Wolfgang Karl Härdle, Léopold Simar, Matthias R. Fengler
Description
This textbook presents the tools and concepts used in multivariate data analysis in a style accessible for non-mathematicians and practitioners. Each chapter features hands-on exercises that showcase applications across various fields of multivariate data analysis. These exercises utilize high-dimensional to ultra-high-dimensional data, reflecting real-world challenges in big data analysis.
The textbook has been updated and revised and now includes new chapters on modern machine learning techniques for dimension reduction and data visualization, namely locally linear embedding, distributed stochastic neighborhood embedding, and uniform manifold approximation and projection, which overcome the shortcomings of traditional visualization and dimension reduction techniques.
Applied Multivariate Statistical Analysis Wolfgang Karl Härdle.pdf
(24.27 MB, 需要: RMB 19 元)
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