A Supervised Filter Feature Selection method for mixed data based on Spectral Feature Selection and Information-theory redundancy analysis

•A supervised filter feature selection method for mixed data is introduced•Spectral analysis and Information-theory based feature selection was applied•Relevant and non-redundant features are selected•An evaluation of the proposed method on 40 public datasets was performed•A comprehensive comparison against state-of-the-art methods was made