Optimization of classifier chains via conditional likelihood maximization.

•A general framework is proposed for multi-label classification from the viewpoint of conditional likelihood maximization.•Based on the proposed framework, the popular classifier chains method is optimized in terms of label correlation modeling and multi-label feature selection.•The contribution of the proposed method is demonstrated theoretically and experimentally.