Feature selection for support vector machines via mixed integer linear programming
type: Item
instance of: scholarly article
title: Feature selection for support vector machines via mixed integer linear programming
zbMATH Open document ID: 1354.68226
author: Yong-Cai Geng
author: Sumit K. Garg
published in: Information Sciences
publication date: 2017-01-31T00:00:00Z
full work available at URL: paperMILPSVM.pdf
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 90C11
zbMATH DE Number: 6679216
zbMATH Keywords: feature selection
zbMATH Keywords: support vector machine
zbMATH Keywords: mixed integer linear programming
describes a project that uses: UCI-ml
MaRDI profile type: Publication
OpenAlex ID: W2062427398
cites work: Multi-group support vector machines with measurement costs: A biobjective approach
cites work: Gene selection for cancer classification using support vector machines
cites work: Imbalanced data classification using second-order cone programming support vector machines
cites work: Q5405165
cites work: A novel feature selection approach: combining feature wrappers and filters
cites work: Q4261789
cites work: 10.1162/153244303322753751
cites work: Linear programming support vector machines
DOI: 10.1016/J.INS.2014.03.110
Recommended article: Mixed integer linear programming for feature selection in support vector machine
Recommended article: Feature selection combining linear support vector machines and concave optimization
Recommended article: Optimal feature selection for support vector machines
Recommended article: Feature selection in the Laplacian support vector machine
Recommended article: Feature selection for linear SVM with provable guarantees
Recommended article: A mixed integer linear programming support vector machine for cost-effective group feature selection: branch-cut-and-price approach
Recommended article: Cost-sensitive feature selection for support vector machines
description: scientific article; zbMATH DE number 6679216