Informative variable identifier: Expanding interpretability in feature selection.

•Interpretability of the solution is provided by a novel feature selection algorithm.•Relevant, redundant and non-informative input variables are identified.•Analysis of weights learned by resampling allows to clarify relations among variables.•Improvement in the interpretability of the results and in classification performance.