Advances in K-means Clustering
A Data Mining Thinking
Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this old algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the dangerous uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides goo…
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Produktdetails
- ISBN: 978-3-642-29807-3
- EAN: 9783642298073
- Produktnummer: 18254237
- Verlag: Springer
- Sprache: Englisch
- Erscheinungsjahr: 2012
- Seitenangabe: 178 S.
- Plattform: PDF
- Masse: 4'576 KB
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