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Escobar CA, Macias D, Morales-Menendez R. Process monitoring for quality - A multiple classifier system for highly unbalanced data. Heliyon. 2021;7(10):e08123doi: 10.1016/j.heliyon.2021.e08123.
Escobar, C. A., Macias, D., & Morales-Menendez, R. (2021). Process monitoring for quality - A multiple classifier system for highly unbalanced data. Heliyon, 7(10), e08123. https://doi.org/10.1016/j.heliyon.2021.e08123
Escobar, Carlos A, et al. "Process monitoring for quality - A multiple classifier system for highly unbalanced data." Heliyon vol. 7,10 (2021): e08123. doi: https://doi.org/10.1016/j.heliyon.2021.e08123
Escobar CA, Macias D, Morales-Menendez R. Process monitoring for quality - A multiple classifier system for highly unbalanced data. Heliyon. 2021 Oct 06;7(10):e08123. doi: 10.1016/j.heliyon.2021.e08123. eCollection 2021 Oct. PMID: 34693053; PMCID: PMC8517167.
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Heliyon. 2021 Oct 06;7(10):e08123. doi: 10.1016/j.heliyon.2021.e08123. eCollection 2021 Oct.

Process monitoring for quality - A multiple classifier system for highly unbalanced data.

Heliyon

Carlos A Escobar, Daniela Macias, Ruben Morales-Menendez

Affiliations

  1. Global Research & Development, General Motors, Warren, MI, USA.
  2. Tecnolo´gico de Monterrey, Monterrey, NL, Mexico.

PMID: 34693053 PMCID: PMC8517167 DOI: 10.1016/j.heliyon.2021.e08123

Abstract

In

© 2021 The Author(s).

Keywords: Binary classification; Defect detection; Ensemble learning; Machine learning; Manufacturing; Meta-learning; Multiple classifier system; Quality control; Unbalanced data

Conflict of interest statement

The authors declare no conflict of interest.

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