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A Survey on Methods for Solving Data Imbalance Problem for Classification

by Arpit Singh, Anuradha Purohit
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 127 - Number 15
Year of Publication: 2015
Authors: Arpit Singh, Anuradha Purohit
10.5120/ijca2015906677

Arpit Singh, Anuradha Purohit . A Survey on Methods for Solving Data Imbalance Problem for Classification. International Journal of Computer Applications. 127, 15 ( October 2015), 37-41. DOI=10.5120/ijca2015906677

@article{ 10.5120/ijca2015906677,
author = { Arpit Singh, Anuradha Purohit },
title = { A Survey on Methods for Solving Data Imbalance Problem for Classification },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 127 },
number = { 15 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 37-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume127/number15/22809-2015906677/ },
doi = { 10.5120/ijca2015906677 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:18:09.091540+05:30
%A Arpit Singh
%A Anuradha Purohit
%T A Survey on Methods for Solving Data Imbalance Problem for Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 127
%N 15
%P 37-41
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The term “data imbalance” in classification is a well established phenomenon in which data set contains unbalanced class distributions. Dataset is called unbalanced if it contains at least one class which is presented by very few examples. A range of solutions have been proposed for the problem of data imbalance including data sampling, cost evaluation of model, bagging, boosting, Genetic Programming (GP) based methods etc. This paper presents a survey of various methods introduced by researchers to handle data imbalance problem in order to improve classification performance and further the comparison between the methods on the basis of their advantages and disadvantages is done.

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Index Terms

Computer Science
Information Sciences

Keywords

Classification data imbalance genetic programming boosting bagging sampling.

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