Structural risk minimization

Known as: SRM 
Structural risk minimization (SRM) is an inductive principle of use in machine learning. Commonly in machine learning, a generalized model must be… (More)
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2010
2010
Structural risk minimization (SRM) (Vapnik and Chervonenkis 1974) is an inductive principle for model selection used for learning… (More)
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2010
2010
Statistical Learning Theory is commonly regarded as a sound framework within which we handle a variety of learning problems in… (More)
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2006
2006
In this paper, the idea of the structural risk minimization (SRM) on credibility space is presented; two theorems are proven to… (More)
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2002
2002
Classificationtreesareoneof themostpopulartypesof classifiers,with easeof implementationand interpretationbeingamongtheir… (More)
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Highly Cited
2001
2000
2000
Estimation of regression functions from bounded, independent and identically distributed data is considered. Motivated by Vapnik… (More)
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Highly Cited
1998
Highly Cited
1998
The paper introduces some generalizations of Vapnik’s method of structural risk minimisation (SRM). As well as making explicit… (More)
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1997
1997
Perceptron Decision Trees also known as Linear Machine DTs etc are analysed in order that data dependent Structural Risk… (More)
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Highly Cited
1991
Highly Cited
1991
The method of Structural Risk Minimization refers to tuning the capacity of the classifier to the available amount of training… (More)
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Highly Cited
1991
Highly Cited
1991
Learning is posed as a problem of function estimation, for which two principles of solution are considered: empirical risk… (More)
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