Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms.

In feature cost scenarios, where a total budget has to be met, common feature selection algorithms are often not suitable to identify well performing subsets for a modelling task. Adaptations of these algorithms such as the ones proposed in this paper can help to tackle this problem.