Machine Learning Modeling Data Locally and Globally
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...
Main Authors: | , , , |
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Format: | eBook |
Language: | English |
Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2008, 2008
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Edition: | 1st ed. 2008 |
Series: | Advanced Topics in Science and Technology in China
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
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