892 search results - page 26 / 179 » On Feature Selection through Clustering |
KDD
2007
ACM
14 years 8 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
ICMCS
1999
IEEE
13 years 12 months ago
1999
IEEE
In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper descr...
ICML
2007
IEEE
14 years 8 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 ...
TNN
2010
13 years 2 months ago
2010
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
ACIVS
2009
Springer
14 years 2 months ago
2009
Springer
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...