A comprehensive reference for researchers in machine learning, data mining, and computer vision, this book presents in-depth, systematic discussions on algorithms and applications for dimensionality reduction. It covers emerging models for general dimensionality reduction in multi-label classification. The book also presents a novel framework to unify a variety of models. Based on the discussions of the models and theory, the authors provide thorough analysis and comparison of the algorithms used in these models. They also include applications of these models and algorithms in bioinformatics and biomedical informatics. A supporting website provides updated information.