Automatic Subspace Clustering

Name: Automatic Subspace Clustering
Brand: Sudwestdeutscher Verlag Fur Hochschulschriften AG
SKU: 9783838138305
Price: 288.1 RON
Availability: InStock

for High-Dimensional Data

Autor: Jiwu Zhao

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Editura: Sudwestdeutscher Verlag Fur Hochschulschriften AG

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Clustering is an important task of data mining. The traditional clustering approaches are designed f...

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Autor

Jiwu Zhao

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2014

Pagini

144

EAN

9783838138305

ISBN

3838138309

Enbook ID

07165652

Editura

Sudwestdeutscher Verlag Fur Hochschulschriften AG

Greutate

222

Dimensiuni

152 x 229 x 9

Descriere completă

Clustering is an important task of data mining. The traditional clustering approaches are designed for searching clusters in the entire space. However, there are usually many irrelevant attributes for clustering in high-dimensional data sets, where the traditional clustering methods often work improperly. Subspace clustering is an extension of traditional clustering that enables finding subspace clusters only in relevant dimensions within a data set. Most subspace clustering methods usually suffer from the issue that their complicated parameter settings are almost troublesome to be determined, and therefore it can be difficult to implement these methods in practical applications. In this book, we introduce two novel subspace clustering methods SUGRA and ASCDD. Both of them are designed with the principle of uncomplicated parameter setting and easy applicability.

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Automatic Subspace Clustering

for High-Dimensional Data

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