1313 search results - page 172 / 263 » Dimensionality Reduction for Classification |
119
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ESANN
2007
15 years 4 months ago
2007
Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
141
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ESANN
2007
15 years 4 months ago
2007
We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...
155
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NIPS
2008
15 years 4 months ago
2008
Principal Components Analysis (PCA) has become established as one of the key tools for dimensionality reduction when dealing with real valued data. Approaches such as exponential ...
103
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NIPS
2007
15 years 4 months ago
2007
Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
119
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SDM
2003
SIAM
15 years 4 months ago
2003
SIAM
We present two extensions of the algorithm by Broomhead et al [2] which is based on the idea that singular values that scale linearly with the radius of the data ball can be explo...