165 search results - page 5 / 33 » Adaptive dimension reduction for clustering high dimensional... |
121
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PODS
2001
ACM
15 years 9 months ago
2001
ACM
The dimensionality curse has profound e ects on the effectiveness of high-dimensional similarity indexing from the performance perspective. One of the well known techniques for im...
113
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PAMI
2011
14 years 4 months ago
2011
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
75
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ICML
2007
IEEE
15 years 10 months ago
2007
IEEE
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...
89
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ADMA
2008
Springer
14 years 11 months ago
2008
Springer
We investigate the effects of dimensionality reduction using different techniques and different dimensions on six two-class data sets with numerical attributes as pre-processing fo...
CIDM
2007
IEEE
15 years 3 months ago
2007
IEEE
Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...