| 書目名稱 | Modern Multivariate Statistical Techniques | | 副標題 | Regression, Classifi | | 編輯 | Alan J. Izenman | | 視頻video | http://file.papertrans.cn/638/637295/637295.mp4 | | 概述 | Describes database management systems for maintaining and querying large databases.Provides detailed descriptions of linear and nonlinear data-mining and machine-learning techniques.Integrates theory, | | 叢書名稱 | Springer Texts in Statistics | | 圖書封面 |  | | 描述 | .Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics. ..These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion o | | 出版日期 | Textbook 2008 | | 關鍵詞 | Boosting; Clustering; Factor analysis; Latent variable model; Linear discriminant analysis; Mathematica; P | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-78189-1 | | isbn_softcover | 978-1-4939-3832-2 | | isbn_ebook | 978-0-387-78189-1Series ISSN 1431-875X Series E-ISSN 2197-4136 | | issn_series | 1431-875X | | copyright | Springer-Verlag New York 2008 |
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