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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Détails bibliographiques
Cote:Libro Electrónico
Auteurs principaux: Huang, Kai-Zhu (Auteur), Yang, Haiqin (Auteur), King, Irwin (Auteur), Lyu, Michael R. (Auteur)
Collectivité auteur: SpringerLink (Online service)
Format: Électronique eBook
Langue:Inglés
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Édition:1st ed. 2008.
Collection:Advanced Topics in Science and Technology in China,
Sujets:
Pattern recognition systems.
Information storage and retrieval systems.
Data mining.
Automated Pattern Recognition.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Accès en ligne:Texto Completo
Table des matières:
  • 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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