ClassificationClassification which is used to predict the classes of objects has the disadvantage of ignoring the costsCost incurred in false predictionsPrediction. However, wrong predictionsPrediction can cause different degrees of costsCost. Therefore, cost-sensitiveCost-sensitiveclassificationClassification algorithms are in demand in order to improve qualityQuality of the classification. In this study, rule-based cost sensitiveCost-sensitiveBEE-minerBEE-miner algorithm which was developed by making use of Bees AlgorithmBees Algorithmand MEPAR-minerMEPAR-miner algorithms are used to classify the defectsDefects in the production line of a textileTextile,Production,Rule-based company in a considerably better way. When results on the qualityQuality defect dataset are analysed, it is observed that BEE-minerBEE-miner algorithm outperforms the MEPAR-minerMEPAR-miner algorithm in terms of classificationClassificationcostCost and accuracy.
A Case Study with the BEE-Miner Algorithm: Defects on the Production Line
Springer Ser.Advanced Manufacturing
Intelligent Production and Manufacturing Optimisation—The Bees Algorithm Approach ; Chapter : 4 ; 63-77
2022-11-20
15 pages
Article/Chapter (Book)
Electronic Resource
English
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