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EN
Purpose: The main goal of the article is to develop a method that automatically allocates the warehouse zones of the product range of the studied enterprise for the selected machine learning algorithm. Design/methodology/approach: The problem of the studied issue is presented in the context of a specific company. The research used the double ABC method for the initial classification of zones. Input data were prepared according to the developed methodology. Selected machine learning algorithms were tested for the same data. Findings: Machine learning methods can be used to classify storage zones in that specific warehouse. Especially Boosted Trees and Neural Networks gives small errors at training stage witch our methodology. There may be differences in errors at the stage of learning the algorithm and the stage of implementing it with completely new data. Originality/value: Machine learning is a new solution that is increasingly used in various areas of logistics. The article draws attention to some problems in implementing this solution for enterprises.
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