429 search results - page 1 / 86 » Unsupervised feature selection for principal components anal... |
KDD
2008
ACM
14 years 5 months ago
2008
ACM
ICDM
2006
IEEE
13 years 11 months ago
2006
IEEE
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
CIBCB
2006
IEEE
13 years 6 months ago
2006
IEEE
In recent years, unsupervised gene (feature) selection has become an integral part of microarray analysis because of the large number of genes and complexity in biological systems....
CORR
2007
Springer
13 years 4 months ago
2007
Springer
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
ICRA
2008
IEEE
13 years 11 months ago
2008
IEEE
— We present a fast feature selection algorithm suitable for object detection applications where the image being tested must be scanned repeatedly to detected the object of inter...