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- W2550871364 abstract "Prediction of customer failure rates plays an important role for establishing appropriate management policies and improving the profitability for industries. For these reasons, many LCD (Liquid crystal display) manufacturing industries have attempted to construct prediction models for customer failure rates. However, most traditional models are based on the parametric approaches requiring the assumption that the data follow a certain probability distribution. To address the limitation posed by the distributional assumption underpinning traditional models, we propose using parameter-free data mining models for predicting customer failure rates. In addition, we use various information associated with product attributes and field return for more comprehensive analysis. The effectiveness and applicability of the proposed method were demonstrated with a real dataset from one of the leading LCD companies in South Korea." @default.
- W2550871364 created "2016-11-30" @default.
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- W2550871364 date "2016-10-15" @default.
- W2550871364 modified "2023-09-25" @default.
- W2550871364 title "Prediction of Customer Failure Rate Using Data Mining in the LCD Industry" @default.
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- W2550871364 doi "https://doi.org/10.7232/jkiie.2016.42.5.327" @default.
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