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Feature Selection for High-Dimensional Data by Veronica Bolon-Canedo, Amparo Alonso-Betanzos, Noelia Sanchez-Marono (Hardcover, 2015)

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About this product

Product Information

This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data. The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers. The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.

Product Identifiers

PublisherSpringer International Publishing A&G

ISBN-139783319218571

eBay Product ID (ePID)223162404

Product Key Features

Number of Pages147 Pages

LanguageEnglish

Publication NameFeature Selection for High-Dimensional Data

Publication Year2015

SubjectComputer Science

TypeTextbook

AuthorVeronica Bolon-Canedo, Amparo Alonso-Betanzos, Noelia Sanchez-Marono

SeriesArtificial Intelligence: Foundations, Theory, and Algorithms

FormatHardcover

Dimensions

Item Height235 mm

Item Weight3731 g

Item Width155 mm

Additional Product Features

Country/Region of ManufactureSwitzerland

Title_AuthorAmparo Alonso-Betanzos, Veronica Bolon-Canedo, Noelia Sanchez-Marono