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portada Computational Methods of Feature Selection
Type
Physical Book
Publisher
Author
Year
2007
Language
English
Pages
440
Format
Hardcover
Dimensions
23.6x16.4x2.9 cm
Weight
0.75 kg.
ISBN
1584888784
ISBN13
9781584888789
Edition No.
1
Categories

Computational Methods of Feature Selection

Liu, Huan ; Motoda, Hiroshi (Author) · CRC Press · Hardcover

Computational Methods of Feature Selection - Liu, Huan ; Motoda, Hiroshi

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Synopsis "Computational Methods of Feature Selection"

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.

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