In this paper we discuss problems of constructing classifiers from imbalanced data. We describe a new approach to selective preprocessing of imbalanced data which combines local ov...
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
In this paper, we propose a linear discriminant analysis (LDA)-based compound distance measure for discriminating similar characters in handwritten Chinese character recognition. ...
This paper proposes an evolutionary RBF network classifier for polarimetric synthetic aperture radar ( SAR) images. The proposed feature extraction process utilizes the full covar...
We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like...