1313 search results - page 56 / 263 » Dimensionality Reduction for Classification |
118
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ICML
2004
IEEE
16 years 3 months ago
2004
IEEE
Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
148
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SIGIR
2004
ACM
15 years 8 months ago
2004
ACM
Document representation and indexing is a key problem for document analysis and processing, such as clustering, classification and retrieval. Conventionally, Latent Semantic Index...
140
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SSPR
2004
Springer
15 years 8 months ago
2004
Springer
We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for...
119
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AUSAI
2006
Springer
15 years 6 months ago
2006
Springer
In this paper, we propose the Kernel Laplacian Eigenmaps for nonlinear dimensionality reduction. This method can be extended to any structured input beyond the usual vectorial data...
141
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BMVC
2010
15 years 1 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...