Feature Selection for Data and Pattern Recognition

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ISBN 10: 3662456192 / ISBN 13: 9783662456194

Verlag: Springer Berlin Heidelberg, 2015

Beschreibung

Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Bestandsnummer des Verkäufers 25122817/2

Bibliografische Details

• Titel: Feature Selection for Data and Pattern Recognition
• Verlag: Springer Berlin Heidelberg
• Erscheinungsjahr: 2015
• Sprache: Englisch
• ISBN-10: 3662456192
• ISBN-13: 9783662456194
• Einband: Hardcover
• Zustand: Sehr gut
• Verkäuferkataloge:
  • Bücher

Über diesen Titel

Inhaltsangabe

This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition.

Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks.

This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.

Von der hinteren Coverseite

<p>This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. </p><p>Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks. </p><p>This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies. </p><p></p>