1.

Record Nr.

UNINA9910830700803321

Autore

Albalate Amparo

Titolo

Semi-supervised and unsupervised machine learning : novel strategies / / Amparo Albalate, Wolfgang Minker

Pubbl/distr/stampa

London, : ISTE, [2011]

ISBN

1-118-55769-7

1-299-13991-4

1-118-58633-6

1-118-58613-1

Descrizione fisica

1 online resource (320 pages)

Collana

ISTE

Disciplina

006.312

Soggetti

Data mining

Discourse analysis - Statistical methods

Speech processing systems

Computational intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

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.

Sommario/riassunto

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 mic