Elena Barzizza, Nicolò Biasetton, Marta Disegna, Alberto Molena, Luigi Salmaso

Abstract:

In this research project a real case-study based on an ensemble Machine Learning algorithm aims to predict the lead time of a product is presented. Specifically, the prediction has been achieved by employing a clustering algorithm as a pre-processing method and comparing several supervised Machine Learning algorithms to determine which one is most suitable for the industry under analysis. The primary aim of this article is to assess the effectiveness of the fuzzy clustering algorithm in enhancing the performance of the prediction algorithm. Our analysis reveals that the Random Forest yields more accurate prediction. Furthermore, the application of a fuzzy clustering algorithm as pre-processing method proves to be advantageous in terms of predictive accuracy.

Keywords: Lead time, Fuzzy clustering, Predictive models, Ensemble Machine Learning algorithm.

Date Published: February 27, 2024
DOI: 10.11159/jmids.2024.003

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