Selection of Objective Function For Imbalanced Classification: An Industrial Case Study

Abdul Rauf Khan, Henrik Schiøler, Murat Kulahci

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-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 publication2017 22nd IEEE International Conference on Emerging Technologies & Factory Automation (EFTA)
PublisherIEEE
Publication date2018
ISBN (Print)978-1-5090-6506-6
ISBN (Electronic)978-1-5090-6505-9
DOIs
Publication statusPublished - 2018
EventIEEE Conference on Emerging Technologies & Factory Automation - Limassol, Cyprus
Duration: 12 Sept 201715 Sept 2017
https://www.etfa2017.org/

Conference

ConferenceIEEE Conference on Emerging Technologies & Factory Automation
Country/TerritoryCyprus
CityLimassol
Period12/09/201715/09/2017
Internet address
SeriesI E E E International Conference on Emerging Technologies and Factory Automation. Proceedings
ISSN1946-0759

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