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 ...
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...
Abstract. We present a new method for analyzing classifiers by visualization, which we call visual nonlinear discriminant analysis. Classifiers that output posterior probabilities ...
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...
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...