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- W2384565464 abstract "Support vector machine is a new kind of machine learning method.This machine learning method is basis of the statistical theories and the structure risk minimum principle,having favorable capabilities of universality and generalization.The support vector machines transform the learning of classifiers problem to the quadratic programming problem which computationally demanding processing of a large amounts of data and slow speed.Geometric algorithm lies on the geometric information of training sets and geometry meaning to solve problem,it easy to apply and has virtues of visualization,high precision and so on.After making an overview towards support vector classifier machine's theories,this text carries the first research step on the geometric algorithms for support vector machines and analyzes their virtues and shortcomings." @default.
- W2384565464 created "2016-06-24" @default.
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- W2384565464 date "2007-01-01" @default.
- W2384565464 modified "2023-09-24" @default.
- W2384565464 title "A Research of Geometry Algorithms for Support Vector Machines" @default.
- W2384565464 hasPublicationYear "2007" @default.
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