A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
We illustrate basic features of the Lixto wrapper generator such as the user and system interaction, the capacious visual interface, the marking and selecting procedures, and the ...
Abstract. Feature subset selection is an important subject when training classifiers in Machine Learning (ML) problems. Too many input features in a ML problem may lead to the so-...
A novel approach to combining clustering and feature selection is presented. It implements a wrapper strategy for feature selection, in the sense that the features are directly se...
Within the taxonomy of feature extraction methods, recently the Wrapper approaches lost some popularity due to the associated computational burden, compared to Embedded or Filter m...
Erik Schaffernicht, Volker Stephan, Horst-Michael ...