—Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning syst...
Feature selection is a problem of choosing a subset of relevant features. Researchers have been searching for optimal feature selection methods. `Branch and Bound' and Focus a...
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...
Poor quality images can significantly affect the accuracy of iris-recognition systems because they do not have enough feature information. However, existing quality measures have f...
Abstract— Feature Selection (FS) is a technique for dimensionality reduction. Its aims are to select a subset of the original features of a dataset which are rich in the most use...