BSVM: A Banded Suport Vector Machine

07/12/2011
by   Gautam V. Pendse, et al.
0

We describe a novel binary classification technique called Banded SVM (B-SVM). In the standard C-SVM formulation of Cortes et al. (1995), the decision rule is encouraged to lie in the interval [1, ∞]. The new B-SVM objective function contains a penalty term that encourages the decision rule to lie in a user specified range [ρ_1, ρ_2]. In addition to the standard set of support vectors (SVs) near the class boundaries, B-SVM results in a second set of SVs in the interior of each class.

READ FULL TEXT
research
06/02/2021

Improvement over Pinball Loss Support Vector Machine

Recently, there have been several papers that discuss the extension of t...
research
08/02/2016

One-Class Slab Support Vector Machine

This work introduces the one-class slab SVM (OCSSVM), a one-class classi...
research
08/23/2018

Multiclass Universum SVM

We introduce Universum learning for multiclass problems and propose a no...
research
02/08/2017

A Modified Construction for a Support Vector Classifier to Accommodate Class Imbalances

Given a training set with binary classification, the Support Vector Mach...
research
09/21/2019

Single Class Universum-SVM

This paper extends the idea of Universum learning [1, 2] to single-class...
research
02/22/2013

Accelerated Linear SVM Training with Adaptive Variable Selection Frequencies

Support vector machine (SVM) training is an active research area since t...
research
06/05/2019

Enumeration of Distinct Support Vectors for Interactive Decision Making

In conventional prediction tasks, a machine learning algorithm outputs a...

Please sign up or login with your details

Forgot password? Click here to reset