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CORR
2007
Springer
198views Education» more  CORR 2007»
13 years 10 months ago
Clustering and Feature Selection using Sparse Principal Component Analysis
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...
Ronny Luss, Alexandre d'Aspremont
ARTMED
2007
347views more  ARTMED 2007»
13 years 10 months ago
A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature
Objective: This study investigates the use of automated pattern recognition methods on magnetic resonance data with the ultimate goal to assist clinicians in the diagnosis of brai...
Jan Luts, Arend Heerschap, Johan A. K. Suykens, Sa...
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
14 years 10 months ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen
CVPR
2004
IEEE
14 years 2 months ago
Face Localization via Hierarchical CONDENSATION with Fisher Boosting Feature Selection
We formulate face localization as a Maximum A Posteriori Probability(MAP) problem of finding the best estimation of human face configuration in a given image. The a prior distribu...
Jilin Tu, ZhenQiu Zhang, Zhihong Zeng, Thomas S. H...
AUSDM
2007
Springer
173views Data Mining» more  AUSDM 2007»
14 years 4 months ago
The Use of Various Data Mining and Feature Selection Methods in the Analysis of a Population Survey Dataset
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Ellen Pitt, Richi Nayak