Springer Publications： Machine Learning: Modeling Data Locally and Globally

Machine Learning: Modeling Data Locally and Globally
by Kai-Zhu Huang, Hai-Qin Yang, Irwin King, Michael Lyu
English | 2008 | ISBN: 3540794514 | 300 pages | PDF | 2.24 MB

MachineLearning - Modeling Data Locally and Globally presents a novel and unifiedtheory that tries to seamlessly integrate different algorithms. Specifically,the book distinguishes the inner nature of machine learning algorithms aseither "local learning "or "global learning."This theorynot only connects previous machine learning methods, or serves as roadmap invarious models, but – more importantly – it also motivates a theory that canlearn from data both locally and globally. This would help the researchers gaina deeper insight and comprehensive understanding of the techniques in thisfield. The book reviews current topics, new theories and applications.