The selection of features for classification, clustering and approximation is an important task in pattern recognition, data mining and soft computing. For real-valued features, th...
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...
We introduce a new framework for the automatic selection of the best views of 3D models. The approach is based on the assumption that models belonging to the same class of shapes ...
High-dimensional collections of 0-1 data occur in many applications. The attributes in such data sets are typically considered to be unordered. However, in many cases there is a n...
Discovering accurate and interesting classification rules is a significant task in the post-processing stage of a data mining (DM) process. Therefore, an optimization problem exis...