2011, ISBN: 9783844399240

[ED: Taschenbuch / Paperback], [PU: Dictus Publishing], In recent years, data have become increasingly larger in both number of instances and number of features in many applications. This… Más…

[ED: Taschenbuch / Paperback], [PU: Dictus Publishing], In recent years, data have become increasingly larger in both number of instances and number of features in many applications. This enormity may cause serious problems to many machine learning algorithms with respect to scalability and learning performance. Therefore, feature selection is essential for the machine learning algorithms while handling high dimensional datasets. Many traditional search methods have shown promising results in a number of feature selection problems. However, as the number of features increases extremely, most of these existing methods face the problem of intractable computational time. Since no single feature selection method could handle all requirements of feature selection in real world datasets, hybrid methods prsented here are the tested methods for effecive Feature Selection.One viable option is to apply a ranking feature selection method to obtain a manageable number of top ranked features which could be further handled by traditional feature selection methods for further analysis., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 64, Selbstabholung und Barzahlung, PayPal, offene Rechnung, Banküberweisung, Internationaler Versand<

ISBN: 9783844399240

In recent years, data have become increasingly larger in both number of instances and number of features in many applications. This enormity may cause serious problems to many machine lea… Más…

In recent years, data have become increasingly larger in both number of instances and number of features in many applications. This enormity may cause serious problems to many machine learning algorithms with respect to scalability and learning performance. Therefore, feature selection is essential for the machine learning algorithms while handling high dimensional datasets. Many traditional search methods have shown promising results in a number of feature selection problems. However, as the number of features increases extremely, most of these existing methods face the problem of intractable computational time. Since no single feature selection method could handle all requirements of feature selection in real world datasets, hybrid methods prsented here are the tested methods for effecive Feature Selection.One viable option is to apply a ranking feature selection method to obtain a manageable number of top ranked features which could be further handled by traditional feature selection methods for further analysis. Bücher, Hörbücher & Kalender / Bücher / Sachbuch / Computer & IT<

2011, ISBN: 9783844399240

Erscheinungsdatum: 06/2011, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Hybrid Methods in Feature Selection: A Data Classification Perspective, Titelzusatz: Hybrid Featu… Más…

Erscheinungsdatum: 06/2011, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Hybrid Methods in Feature Selection: A Data Classification Perspective, Titelzusatz: Hybrid Feature Selection Methods are the proven methods for Large Scale Feature Selection, Autor: Subramanian, Senthamarai Kannan, Verlag: LAP Lambert Acad. Publ., Sprache: Englisch, Rubrik: Informatik // EDV, Sonstiges, Seiten: 64, Informationen: Paperback, Gewicht: 112 gr, Verkäufer: averdo Belletristik<

2011, ISBN: 3844399240

Kartoniert / Broschiert, mit Schutzumschlag 11, [PU:LAP LAMBERT Academic Publishing]

2011, ISBN: 3844399240

Kartoniert / Broschiert, mit Schutzumschlag neu, [PU:LAP Lambert Acad. Publ.]