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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Feature Selection for Knowledge Discovery and Data Mining
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Feature Selection for Knowledge Discovery and Data Mining
Huan Liu, Hiroshi Motoda (Broschiert, Englisch)
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Beschreibung
As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer… technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
27.01.2013
Sprache
Englisch
EAN
9781461376040
Herausgeber
Springer US
Serien- oder Bandtitel
The Springer International Series in Engineering and Computer Science
Sonderedition
Nein
Autor
Huan Liu, Hiroshi Motoda
Seitenanzahl
214
Einbandart
Broschiert
Schlagwörter
data mining, database, knowledge, knowledge discovery, learning, machine learning
Thema-Inhalt
UMB - Algorithmen und Datenstrukturen
GPF - Informationstheorie
UYQ - Künstliche Intelligenz
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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