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035   $a(CaSebORM)9781118586136
035   $a(EXLCZ)992670000000327416
100   $a20130211d2011      uy             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aSemi-supervised and unsupervised machine learning$b[electronic resource] $enovel strategies /$fAmparo Albalate, Wolfgang Minker
205   $a1st edition
210   $aLondon $cISTE ;$aHoboken, N.J. $cWiley$d2011
215   $a1 online resource (256 p.)
225 1 $aISTE
300   $aDescription based upon print version of record.
311   $a1-84821-203-8 
320   $aIncludes bibliographical references and index.
327   $apt. 1. State of the art -- pt. 2. Approaches to semi-supervised classification -- pt. 3. Contributions to unsupervised classification, algorithms to detect the optimal number of clusters.
330   $aThis book provides a detailed and up-to-date overview on classification and data mining methods. The first part is focused on supervised classification algorithms and their applications, including recent research on the combination of classifiers. The second part deals with unsupervised data mining and knowledge discovery, with special attention to text mining. Discovering the underlying structure on a data set has been a key research topic associated to unsupervised techniques with multiple applications and challenges, from web-content mining to the inference of cancer subtypes in genomic mic
410  0$aISTE
606   $aData mining
606   $aDiscourse analysis$xStatistical methods
606   $aSpeech processing systems
606   $aComputational intelligence
608   $aElectronic books.
615  0$aData mining.
615  0$aDiscourse analysis$xStatistical methods.
615  0$aSpeech processing systems.
615  0$aComputational intelligence.
676   $a006.312
700   $aAlbalate$b Amparo$0935691
701   $aMinker$b Wolfgang$0935692
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910141493103321
996   $aSemi-supervised and unsupervised machine learning$92107725
997   $aUNINA