Kernel Methods - Extending SVM to infinite-dimensional spaces using the kernel trick, and to non-separable data using soft margins. Lecture 15 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - [ Ссылка ] and on the course website - [ Ссылка ]
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This lecture was recorded on May 22, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.
Lecture 15 - Kernel Methods
Теги
Machine Learning (Field Of Study)kernel methodsSupport Vector MachineCaltechMOOCdatacomputersciencecourseData Mining (Technology Class)Big DataData Sciencelearning from datakernel trickSVMRBFsoft marginquadratic programmingpolynomial kernelVapnikTechnology (Professional Field)Computer Science (Industry)Learning (Quotation Subject)Lecture (Type Of Public Presentation)California Institute Of Technology (Organization)Abu-MostafaYaser