Relevance, redundancy, and complementarity trade-off (RRCT): A principled, generic, robust feature-selection tool.

ABSTRACT: We present a new heuristic feature-selection (FS) algorithm that integrates in a principled algorithmic framework the three key FS components: relevance, redundancy, and complementarity. Thus, we call it relevance, redundancy, and complementarity trade-off (RRCT). The association strength between each feature and the response and between feature pairs is quantified via an information theoretic transformation of rank correlation coefficients, and the feature complementarity is quantified using partial correlation coefficients. We empirically benchmark the performance of RRCT against 19 FS algorithms across four synthetic and eight real-world datasets in indicative challenging settings evaluating the following: (1) matching the true feature set and (2) out-of-sample performance in binary and

SUBMITTER: Tsanas A 

PROVIDER: S-EPMC9122960 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature