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

Publication: Research - peer-reviewArticle in proceeding

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.
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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 publicationIEEE International Conference on Emerging Technology & Factory Automation
PublisherIEEE
Publication date2017
StatePublished - 2017
EventIEEE Conference on Emerging Technologies & Factory Automation - Limassol, Cyprus

Conference

ConferenceIEEE Conference on Emerging Technologies & Factory Automation
LandCyprus
ByLimassol
Periode12/09/201715/09/2017
Internetadresse

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ID: 260405019