Machine Learning : Modeling Data Locally and Globally
- Author
- Kaizhu Huang, Haiqin Yang, Irwin King …
- Publication Year
- 2008
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Computer Science
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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."This theory not only connects previous machine learning methods, or serves as roadmap in various models, but – more importantly – it also motivates a theory that can learn from data both locally and globally. This would help the researchers gain a deeper insight and comprehensive understanding of the techniques in this field. The book reviews current topics,new theories and applications.
Keywords: Computer science / ATSTC / Global learning / Hybrid learning / Kernelization / Local learning / ZJUP / Algorithms / Computer science / Machine learning / Pattern Recognition / Information Storage and Retrieval / Data Mining and Knowledge Discovery
