Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning (Springer Texts in Statistics)
| Author | : | |
| Rating | : | 4.93 (840 Votes) |
| Asin | : | 0387781889 |
| Format Type | : | paperback |
| Number of Pages | : | 733 Pages |
| Publish Date | : | 2016-09-19 |
| Language | : | English |
DESCRIPTION:
Material such as database management systems is included that has never appeared in statistics books before.. This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data
… Another unique feature of this book is the discussion of database management systems. The goal is to present the current state of the art in multivariate analysis methods while attempting to place them on a firm statistical basis. 52, 2011). This book is appropiate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics and engineering. More than 200 exercises are presented in the book." (J. (2009).” (Journal of the Royal Statistical Society)“In Mod
A great step forward in the way we look at multivariate data This book surprised me. I was expecting a book filled with a discussion of mostly traditional multivariate techniques supplemented by a few chapters of more recent developments. Instead, I found a completely new and refreshing approach to statistics and data exploration that framed the classical regression approach to most issues as a special, limiting case of a. "nice reference" according to Tseng, Chien-han. This book not only covers very wide ranges about ststistical learning but also has very deep discriptions in some topics. This is a good book especially for graduate students.. "Nice material or PhD students" according to Dmitry SHALYMOV. Good observation of modern approaches for classification and clustering problems. Nice structure of material and nice paper =)