Feature selection for high dimensional data artificial intelligence foundations theory and algorithms veronica bolon canedo noelia sanchez marono amparo alonso betanzos on amazoncom free shipping on qualifying offers this book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems. The following outline is provided as an overview of and topical guide to machine learning machine learning is a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence in 1959 arthur samuel defined machine learning as a field of study that gives computers the ability to learn without . Feature selection for high dimensional data feature selection for high dimensional data artificial intelligence foundations theory and algorithms hardcover october 3 2015 feature selection for high dimensional where m is the number of data points then we use the coefficient of determination or 2 to enforce a. And synthesis of feature selection algorithms presenting a comprehensive review of basic concepts and experimental results of the most well known algorithms sec ond an interesting novelty and contribution of the book is how it addresses different real scenarios with high dimensional data showing the use of feature selection algo. Veronica bolon canedo noelia sanchez marono amparo alonso betanzos feature selection for high dimensional data artificial intelligence foundations theory and algorithms springer 2015 isbn 978 3 319 21857 1 pp 1 132
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