Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
In this paper we present a minimum sphere covering approach to pattern classification that seeks to construct a minimum number of spheres to represent the training data and formul...
We present a novel multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility in detect...
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...