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IJCAI
2007
13 years 9 months ago
Locality Sensitive Discriminant Analysis
Linear Discriminant Analysis (LDA) is a popular data-analytic tool for studying the class relationship between data points. A major disadvantage of LDA is that it fails to discove...
Deng Cai, Xiaofei He, Kun Zhou, Jiawei Han, Hujun ...
BMCBI
2005
167views more  BMCBI 2005»
13 years 7 months ago
Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes
Background: The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer...
Patrick Warnat, Roland Eils, Benedikt Brors
ESANN
2006
13 years 9 months ago
Visual nonlinear discriminant analysis for classifier design
Abstract. We present a new method for analyzing classifiers by visualization, which we call visual nonlinear discriminant analysis. Classifiers that output posterior probabilities ...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda
ICASSP
2010
IEEE
13 years 7 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi
SIBGRAPI
2009
IEEE
14 years 2 months ago
A Multi-linear Discriminant Analysis of 2D Frontal Face Images
We have designed and implemented a multi-linear discriminant method of constructing and quantifying statistically significant changes on human identity photographs. The method is...
Carlos E. Thomaz, Vagner do Amaral, Gilson Antonio...