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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...

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Bibliographic Details
Main Authors: Huang, Kai-Zhu, Yang, Haiqin (Author), King, Irwin (Author), Lyu, Michael R. (Author)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2008, 2008
Edition:1st ed. 2008
Series:Advanced Topics in Science and Technology in China
Subjects:
Information Storage And Retrieval
Data Mining
Information Storage And Retrieval Systems
Data Mining And Knowledge Discovery
Automated Pattern Recognition
Pattern Recognition Systems
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

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