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Can I read High-dimensional Clustering Using Frequency Sensitive Competitive Learning on EtoBox?
High-dimensional Clustering Using Frequency Sensitive Competitive Learning by P. Scheunders; S. De Backer is a Computer Science article available to read on EtoBox.
What is High-dimensional Clustering Using Frequency Sensitive Competitive Learning about?
In this paper a clustering algorithm for sparsely sampled high-dimensional feature spaces is proposed. The algorithm performs clustering by employing a distance measure that compensates for differently sized clusters. A sequential version of the algorithm is constructed in the form of a frequency-sensitive competitive learning scheme. Experiments are conducted on an artificial Gaussian data set and on wavelet-based texture feature sets, where classification performance is used as a clustering significance measure. It is shown that the proposed technique improves classification performance dramatically for high-dimensional problems.
Who reads High-dimensional Clustering Using Frequency Sensitive Competitive Learning?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- P. Scheunders; S. De Backer
- Publisher
- Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0031-3203)
- Published
- 1999
- Language
- EN
- Field
- Computer Science (Physical Sciences)