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

Abdul Rauf Khan; Henrik Schiøler; Murat Kulahci

doi:10.1109/ETFA.2017.8396223

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

Abdul Rauf Khan, Henrik Schiøler, Murat Kulahci

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer 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.

Originalsprog	Engelsk
Titel	2017 22nd IEEE International Conference on Emerging Technologies & Factory Automation (EFTA)
Forlag	IEEE
Publikationsdato	2018
ISBN (Trykt)	978-1-5090-6506-6
ISBN (Elektronisk)	978-1-5090-6505-9
DOI	https://doi.org/10.1109/ETFA.2017.8396223
Status	Udgivet - 2018
Begivenhed	IEEE Conference on Emerging Technologies & Factory Automation - Limassol, Cypern Varighed: 12 sep. 2017 → 15 sep. 2017 https://www.etfa2017.org/

Konference

Konference	IEEE Conference on Emerging Technologies & Factory Automation
Land/Område	Cypern
By	Limassol
Periode	12/09/2017 → 15/09/2017
Internetadresse	https://www.etfa2017.org/

Navn	I E E E International Conference on Emerging Technologies and Factory Automation. Proceedings
ISSN	1946-0759

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10.1109/ETFA.2017.8396223

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title = "Selection of Objective Function For Imbalanced Classification: An Industrial Case Study",

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.",

author = "Khan, {Abdul Rauf} and Henrik Schi{\o}ler and Murat Kulahci",

year = "2018",

doi = "10.1109/ETFA.2017.8396223",

language = "English",

isbn = "978-1-5090-6506-6",

series = "I E E E International Conference on Emerging Technologies and Factory Automation. Proceedings",

booktitle = "2017 22nd IEEE International Conference on Emerging Technologies & Factory Automation (EFTA)",

publisher = "IEEE",

address = "United States",

note = "IEEE Conference on Emerging Technologies & Factory Automation, ETFA 2017 ; Conference date: 12-09-2017 Through 15-09-2017",

url = "https://www.etfa2017.org/",

}

Khan, AR, Schiøler, H & Kulahci, M 2018, Selection of Objective Function For Imbalanced Classification: An Industrial Case Study. i 2017 22nd IEEE International Conference on Emerging Technologies & Factory Automation (EFTA). IEEE, I E E E International Conference on Emerging Technologies and Factory Automation. Proceedings, IEEE Conference on Emerging Technologies & Factory Automation, Limassol, Cypern, 12/09/2017. https://doi.org/10.1109/ETFA.2017.8396223

Selection of Objective Function For Imbalanced Classification: An Industrial Case Study. / Khan, Abdul Rauf; Schiøler, Henrik; Kulahci, Murat.
2017 22nd IEEE International Conference on Emerging Technologies & Factory Automation (EFTA). IEEE, 2018. (I E E E International Conference on Emerging Technologies and Factory Automation. Proceedings).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Selection of Objective Function For Imbalanced Classification

T2 - IEEE Conference on Emerging Technologies & Factory Automation

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AU - Schiøler, Henrik

AU - Kulahci, Murat

PY - 2018

Y1 - 2018

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AB - 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.

U2 - 10.1109/ETFA.2017.8396223

DO - 10.1109/ETFA.2017.8396223

M3 - Article in proceeding

SN - 978-1-5090-6506-6

T3 - I E E E International Conference on Emerging Technologies and Factory Automation. Proceedings

BT - 2017 22nd IEEE International Conference on Emerging Technologies & Factory Automation (EFTA)

PB - IEEE

Y2 - 12 September 2017 through 15 September 2017

ER -

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

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