Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the basic concepts and principles, state-of-the-art algorithms, and novel applications of this tool.
The book begins by exploring unsupervised, randomized, and causal feature selection. It then reports on some recent results of empowering feature selection, including active feature selection, decision-border estimate, the use of ensembles with independent probes, and incremental feature selection. This is followed by discussions of weighting and local methods, such as the ReliefF family, k-means clustering, local feature relevance, and a new interpretation of Relief. The book subsequently covers text classification, a new feature selection score, and both constraint-guided and aggressive feature selection. The final section examines applications of feature selection in bioinformatics, including feature construction as well as redundancy-, ensemble-, and penalty-based feature selection.
Through a clear, concise, and coherent presentation of topics, this volume systematically covers the key concepts, underlying principles, and inventive applications of feature selection, illustrating how this powerful tool can efficiently harness massive, high-dimensional data and turn it into valuable, reliable information.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Arizona State University, Tempe, AZ AFOSR/AOARD, Tokyo, Japan
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BookOrders, Russell, IA, Etats-Unis
Hard Cover. Etat : Good. No Jacket. Ex-library with the usual features. The interior is clean and tight. Binding and cover are good. 419 pages. Ex-Library. N° de réf. du vendeur 120467
Quantité disponible : 1 disponible(s)
Vendeur : BennettBooksLtd, Los Angeles, CA, Etats-Unis
Hardcover. Etat : New. In shrink wrap. Looks like an interesting title! N° de réf. du vendeur Q-1584888784
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 5100536-n
Quantité disponible : 10 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. pp. 440 This item is printed on demand. N° de réf. du vendeur 7573552
Quantité disponible : 3 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 5100536-n
Quantité disponible : 10 disponible(s)
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Hardback. Etat : New. New copy - Usually dispatched within 4 working days. N° de réf. du vendeur B9781584888789
Quantité disponible : 1 disponible(s)
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Etat : New. PRINT ON DEMAND pp. 440. N° de réf. du vendeur 18274405
Quantité disponible : 4 disponible(s)
Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 440. N° de réf. du vendeur 26274415
Quantité disponible : 4 disponible(s)
Vendeur : moluna, Greven, Allemagne
Gebunden. Etat : New. Huan Liu, Hiroshi MotodaDue to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and. N° de réf. du vendeur 596345176
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 5100536
Quantité disponible : 10 disponible(s)