— One of the main obstacles facing the application of computational intelligence technologies in pattern recognition (and indeed in many other tasks) is that of dataset dimension...
We present a framework that enables the use of traditional feature selection algorithms in a new context - for building a set of subsets of specified properties. During the course...
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
This paper describes an efficient feature selection method that quickly selects a small subset out of a given huge feature set; for building robust object detection systems. In th...
New feature selection algorithms for linear threshold functions are described which combine backward elimination with an adaptive regularization method. This makes them particular...