Machine Learning Modeling Data Locally and Globally /

• Main Authors: Huang, Kaizhu (Author), Yang, Haiqin (Author), King, Irwin (Author), Lyu, Michael (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Series: Advanced Topics in Science and Technology in China,
• Subjects: Computer science.; Data mining.; Information storage and retrieval.; Pattern recognition.; Computer Science.; Pattern Recognition.; Information Storage and Retrieval.; Data Mining and Knowledge Discovery.

Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either "local learning"or "global learning."T...

Table of Contents:

• Global Learning vs. Local Learning
• A General Global Learning Model: MEMPM
• Learning Locally and Globally: Maxi-Min Margin Machine
• Extension I: BMPM for Imbalanced Learning
• Extension II: A Regression Model from M4
• Extension III: Variational Margin Settings within Local Data in Support Vector Regression
• Conclusion and Future Work.