Near-Bayesian support vector machines for imbalanced data classification with equal or unequal misclassification costs
type: Item
instance of: scholarly article
title: Near-Bayesian support vector machines for imbalanced data classification with equal or unequal misclassification costs
zbMATH Open document ID: 1394.68280
author: Shounak Datta
author: Swagatam Das
published in: Neural Networks
publication date: 2018-08-30T00:00:00Z
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 6929305
zbMATH Keywords: support vector machines
zbMATH Keywords: Bayes error
zbMATH Keywords: imbalanced data
zbMATH Keywords: decision boundary shift
zbMATH Keywords: unequal costs
zbMATH Keywords: multi-class classification
describes a project that uses: SMOTE
describes a project that uses: LIBSVM
describes a project that uses: UCI-ml
MaRDI profile type: Publication
full work available at URL: j.neunet.2015.06.005
OpenAlex ID: W1100975233
Wikidata QID: Q30982668
cites work: Machine Learning: ECML 2004
cites work: Q4533353
cites work: Support-vector networks
cites work: Improvements to Platt's SMO Algorithm for SVM Classifier Design
cites work: Support vector machines for classification in nonstandard situations
cites work: Breakthroughs in statistics. Volume I: Foundations and basic theory
cites work: Learning SVM with weighted maximum margin criterion for classification of imbalanced data
DOI: 10.1016/J.NEUNET.2015.06.005
description: scientific article; zbMATH DE number 6929305