Wrapper-based feature selection is attractive because wrapper methods are able to optimize the features they select to the specific learning algorithm. Unfortunately, wrapper met...
In this paper we generalize the LARS feature selection method to the linear SVM model, derive an efficient algorithm for it, and empirically demonstrate its usefulness as a featur...
Building blocks are a ubiquitous feature at all levels of human understanding, from perception through science and innovation. Genetic algorithms are designed to exploit this prev...
With the proliferation of extremely high-dimensional data, feature selection algorithms have become indispensable components of the learning process. Strangely, despite extensive ...
Feature selection is used to improve performance of learning algorithms by finding a minimal subset of relevant features. Since the process of feature selection is computationally ...
Mark Last, Abraham Kandel, Oded Maimon, Eugene Ebe...