Machine Learning Modeling Data Locally and Globally /

• Κύριοι συγγραφείς: Huang, Kaizhu (Συγγραφέας), Yang, Haiqin (Συγγραφέας), King, Irwin (Συγγραφέας), Lyu, Michael (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Σειρά: Advanced Topics in Science and Technology in China,
• Θέματα: 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...

Πίνακας περιεχομένων:

• 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.