Structural risk minimization
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Support vector regression has been applied to stock market forecasting problems. However, it is usually needed to tune manually… Expand Structural risk minimization (SRM) (Vapnik and Chervonenkis 1974) is an inductive principle for model selection used for learning… Expand Statistically distinguishing density-dependent from density-independent populations and selecting the best demographic model for… Expand Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine… Expand We suggest a penalty function to be used in various problems of structural risk minimization. This penalty is data dependent and… Expand The Vicinal Risk Minimization principle establishes a bridge between generative models and methods derived from the Structural… Expand The paper introduces some generalizations of Vapnik's (1982) method of structural risk minimization (SRM). As well as making… Expand We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve… Expand Learning is posed as a problem of function estimation, for which two principles of solution are considered: empirical risk… Expand The method of Structural Risk Minimization refers to tuning the capacity of the classifier to the available amount of training… Expand