Multi-Label Dimensionality Reduction / Edition 1

Addressing this shortfall, covers the methodological developments, theoretical properties, computational aspects, and applications of many multi-label dimensionality reduction algorithms. It explores numerous research questions, including: The authors emphasize their extensive work on dimensionality reduction for multi-label learning. Using a case study of gene expression pattern image annotation, they demonstrate how to apply multi-label dimensionality reduction algorithms to solve real-world problems. A supplementary website provides a MATLAB package for implementing popular dimensionality reduction algorithms.