Selection of objective function for imbalanced classification: an industrial case study

Abdul Rauf Khan, Henrik Schiøler, Murat Kulahci

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this article we discuss the issue of selecting suitable objective function for Genetic Algorithm to solve an imbalanced classification problem. More precisely, first we discuss the need of specialized objective function to solve a real classification problem from our industrial partner and then we compare the results of our proposed objective function with commonly used candidates to serve this purpose. Our comparison is based on the analysis of real data collected during the quality control stages of the manufacturing process.
Original languageEnglish
Title of host publicationProceedings of 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation
Number of pages4
PublisherIEEE
Publication date2017
Pages1-4
ISBN (Print)9781509065059
DOIs
Publication statusPublished - 2017
Event2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation - Grand Resort Hotel, Limassol, Cyprus
Duration: 12 Sep 201715 Sep 2017
Conference number: 22
https://ieeexplore.ieee.org/xpl/conhome/8233358/proceeding?isnumber=8247555

Conference

Conference2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation
Number22
LocationGrand Resort Hotel
Country/TerritoryCyprus
CityLimassol
Period12/09/201715/09/2017
Internet address

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