02808nam 2200673 a 450 991014149310332120170815164255.01-118-55769-71-299-13991-41-118-58633-61-118-58613-1(CKB)2670000000327416(EBL)1117273(OCoLC)827208477(SSID)ssj0000883828(PQKBManifestationID)11454490(PQKBTitleCode)TC0000883828(PQKBWorkID)10924808(PQKB)10950575(OCoLC)826657834(MiAaPQ)EBC1117273(CaSebORM)9781118586136(EXLCZ)99267000000032741620130211d2011 uy 0engur|n|---|||||txtccrSemi-supervised and unsupervised machine learning[electronic resource] novel strategies /Amparo Albalate, Wolfgang Minker1st editionLondon ISTE ;Hoboken, N.J. Wiley20111 online resource (256 p.)ISTEDescription based upon print version of record.1-84821-203-8 Includes bibliographical references and index.pt. 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.This 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 micISTEData miningDiscourse analysisStatistical methodsSpeech processing systemsComputational intelligenceElectronic books.Data mining.Discourse analysisStatistical methods.Speech processing systems.Computational intelligence.006.312Albalate Amparo935691Minker Wolfgang935692MiAaPQMiAaPQMiAaPQBOOK9910141493103321Semi-supervised and unsupervised machine learning2107725UNINA