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» Class Separability in Spaces Reduced By Feature Selection
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PAKDD
2005
ACM
133views Data Mining» more  PAKDD 2005»
14 years 2 months ago
Feature Selection for High Dimensional Face Image Using Self-organizing Maps
: While feature selection is very difficult for high dimensional, unstructured data such as face image, it may be much easier to do if the data can be faithfully transformed into l...
Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Fuyan Zh...
MCS
2007
Springer
14 years 2 months ago
Stopping Criteria for Ensemble-Based Feature Selection
Selecting the optimal number of features in a classifier ensemble normally requires a validation set or cross-validation techniques. In this paper, feature ranking is combined with...
Terry Windeatt, Matthew Prior
CVPR
2005
IEEE
14 years 10 months ago
Selection and Fusion of Color Models for Feature Detection
The choice of a color space is of great importance for many computer vision algorithms (e.g. edge detection and object recognition). It induces the equivalence classes to the actu...
Harro M. G. Stokman, Theo Gevers
GFKL
2005
Springer
105views Data Mining» more  GFKL 2005»
14 years 2 months ago
Variable Selection for Discrimination of More Than Two Classes Where Data are Sparse
In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maxi...
Gero Szepannek, Claus Weihs
CIKM
2008
Springer
13 years 10 months ago
REDUS: finding reducible subspaces in high dimensional data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are...
Xiang Zhang, Feng Pan, Wei Wang 0010