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高维数据分析

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高维数据分析

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作 者:蔡天文. 沈晓桐. 编

出 版 社:高等教育

出版时间:2010-10-1

I S B N:9787040298512

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    《高维数据分析(英文版)》是由高等教育出版社出版的。

    内容简介

    over the last few years, significant developments have been taking place in high-dimensional data analysis, driven primarily by a wide range of applications in many fields such as genomics and signal processing. in particular, substantial advances have been made in the areas of feature selection, covariance estimation,classification and regression. this book intends to examine important issues arising from high-dimensional data analysis to explore key ideas for statistical inference and prediction.
    it is structured around topics on multiple hypothesis testing, feature selection, regression, classification, dimension reduction, as well as applications in survival analysis and biomedical research.
    the book will appeal to graduate students and new researchers interested in the plethora of opportunities available in highdimensional data analysis.

    作者简介

    目录

    preface
    part i high-dimensional classification
     chapter 1 high-dimensional classification jianqing fan, yingying fan and yichao wu
      1 introduction
      2 elements of classifications
      3 impact of dimensionality on classification
      4 distance-based classification rules
      5 feature selection by independence rule
      6 loss-based classification
      7 feature selection in loss-based classification
      8 multi-category classification
      references
     chapter 2 flexible large margin classifiers yufeng liu and yichao wu
      1 background on classification
      2 the support vector machine: the margin formulation and the sv interpretation

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