Matrix factorization or factor analysis is an important task helpful in the analysis of high dimensional real world data. There are several well known methods and algorithms for fa...
Collaborative Filtering (CF) aims at finding patterns in a sparse matrix of contingency. It can be used for example to mine the ratings given by users on a set of items. In this p...
Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by max...
An ever-present problem in intrusion detection technology is how to construct the patterns of (good, bad or anomalous) behaviour upon which an engine have to make decisions regardi...
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...