02856nam 2200661 a 450 991087739950332120200520144314.01-118-55769-71-299-13991-41-118-58633-61-118-58613-1(CKB)2670000000327416(EBL)1117273(SSID)ssj0000883828(PQKBManifestationID)11454490(PQKBTitleCode)TC0000883828(PQKBWorkID)10924808(PQKB)10950575(MiAaPQ)EBC1117273(CaSebORM)9781118586136(OCoLC)826657834(OCoLC)857717622(OCoLC)ocn857717622(EXLCZ)99267000000032741620130211d2011 uy 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierSemi-supervised and unsupervised machine learning novel strategies /Amparo Albalate, Wolfgang MinkerLondon ISTE ;Hoboken, N.J. Wiley20111 online resource (320 pages)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 micInternational Society for Technology in Education.ISTE publicationsData miningDiscourse analysisStatistical methodsSpeech processing systemsComputational intelligenceData mining.Discourse analysisStatistical methods.Speech processing systems.Computational intelligence.6.312Albalate Amparo1750043Minker Wolfgang935692MiAaPQMiAaPQMiAaPQBOOK9910877399503321Semi-supervised and unsupervised machine learning4184564UNINA