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{ "item_title" : "High-Dimensional Data Analysis (V2)", "item_author" : [" Cai Tony "], "item_description" : "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 high-dimensional data analysis.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/81/432/485/981432485X_b.jpg", "price_data" : { "retail_price" : "117.00", "online_price" : "117.00", "our_price" : "117.00", "club_price" : "117.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
High-Dimensional Data Analysis (V2)|Cai Tony

High-Dimensional Data Analysis (V2)

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Overview

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 high-dimensional data analysis.

This item is Non-Returnable

Details

  • ISBN-13: 9789814324854
  • ISBN-10: 981432485X
  • Publisher: Wsp/Other Publr
  • Publish Date: March 2011
  • Dimensions: 9.4 x 6.8 x 0.9 inches
  • Shipping Weight: 1.6 pounds
  • Page Count: 320

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