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» SVM feature selection for multidimensional EEG data
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ICML
2009
IEEE
15 years 10 months ago
Partially supervised feature selection with regularized linear models
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...
Thibault Helleputte, Pierre Dupont
ISMB
2008
14 years 11 months ago
Classification of arrayCGH data using fused SVM
Motivation: Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are...
Franck Rapaport, Emmanuel Barillot, Jean-Philippe ...
ICPR
2006
IEEE
15 years 10 months ago
Adaptive Feature Integration for Segmentation of 3D Data by Unsupervised Density Estimation
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
Marco Cristani, Umberto Castellani, Vittorio Murin...
EVOW
2004
Springer
15 years 2 months ago
Analysis of Proteomic Pattern Data for Cancer Detection
Abstract. In this paper we analyze two proteomic pattern datasets containing measurements from ovarian and prostate cancer samples. In particular, a linear and a quadratic support ...
Kees Jong, Elena Marchiori, Aad van der Vaart
IJCNN
2008
IEEE
15 years 3 months ago
Feature selection based on kernel discriminant analysis for multi-class problems
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
Tsuneyoshi Ishii, Shigeo Abe