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SDM
2008
SIAM
136views Data Mining» more  SDM 2008»
14 years 11 months ago
Exploration and Reduction of the Feature Space by Hierarchical Clustering
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
Dino Ienco, Rosa Meo
SEBD
2008
169views Database» more  SEBD 2008»
14 years 11 months ago
Clustering the Feature Space
Abstract Dino Ienco and Rosa Meo Dipartimento di Informatica, Universit`a di Torino, Italy In this paper we propose and test the use of hierarchical clustering for feature selectio...
Dino Ienco, Rosa Meo
TNN
2010
154views Management» more  TNN 2010»
14 years 4 months ago
Discriminative semi-supervised feature selection via manifold regularization
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 ...
Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin
CVPR
2010
IEEE
15 years 4 months ago
Putting local features on a Manifold
Local features have proven very useful for recognition. Manifold learning has proven to be a very powerful tool in data analysis. However, manifold learning application for imag...
Marwan Torki and Ahmed Elgammal
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
15 years 10 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler