33 search results - page 1 / 7 » A framework for ontology-driven subspace clustering |
CBMS
2005
IEEE
13 years 11 months ago
2005
IEEE
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
CVPR
2012
IEEE
11 years 7 months ago
2012
IEEE
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
ICML
2007
IEEE
14 years 6 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 ...
SDM
2009
SIAM
14 years 2 months ago
2009
SIAM
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
ICDM
2005
IEEE
13 years 11 months ago
2005
IEEE
In this paper, we propose a semi-supervised framework for learning a weighted Euclidean subspace, where the best clustering can be achieved. Our approach capitalizes on user-const...