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182
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ICML
2004
IEEE
16 years 1 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
107
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MCS
2007
Springer
15 years 7 months ago
2007
Springer
In this paper we present a fusion technique for Support Vector Machine (SVM) scores, obtained after a dimension reduction with Bilateralprojection-based Two-Dimensional Principal C...
91
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CEC
2009
IEEE
15 years 7 months ago
2009
IEEE
— This paper attempts to address the question of scaling up Particle Swarm Optimization (PSO) algorithms to high dimensional optimization problems. We present a cooperative coevo...
126
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KDD
2006
ACM
16 years 1 months ago
2006
ACM
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
106
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STOC
2004
ACM
16 years 1 months ago
2004
ACM
The doubling dimension of a metric is the smallest k such that any ball of radius 2r can be covered using 2k balls of raThis concept for abstract metrics has been proposed as a na...