In this paper, a novel linear projection classification technique, termed regularized large margin classifier (RIMC), is developed in this paper.

In this paper, a novel linear projection classification technique, termed regularized large margin classifier (RLMC), is developed in this paper.

Mar 15, 2018 · We present a formulation of deep learning that aims at producing a large margin classifier. The notion of margin, minimum distance to a decision ...

This paper introduces a novel regularization strategy to address the generalization issues for large-margin classifiers from the Empiri- cal Risk Minimization ( ...

In this paper, we unify these classifiers into a common framework from the concept of structural granularity and the formulation for optimization problems.

Fits a regularization path for large margin classifiers at a sequence of regularization parameters lambda. Usage. gcdnet( x, y, nlambda = 100, method = c("hhsvm ...

Support vector machine (SVM), as one of the most popular classifiers, aims to find a hyperplane that can separate two classes of data with maximal margin.

Abstract. In this paper we study boosting methods from a new perspective. We build on recent work by Efron et al. to show that boosting approximately (and ...

Jan 6, 2020 · The goal is to have the largest possible margin between the decision boundary that separates the two classes and the training instances.

Embedded methods use large margin classifiers with a regularization method that shrinks the number of features. These methods generate sparse solutions and ...