This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Predictions computed by a classification tree are usually constant on axis-parallel hyperrectangles corresponding to the leaves and have strict jumps on their boundaries. The densi...
In an interactive classification application, a user may find it more valuable to develop a diagnostic decision support method which can reveal significant classification behavior...
In this paper we tackle the main problem presented by the majority of Information Visualization techniques, that is, the limited number of data items that can be visualized simulta...
Background: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold ...