Prediction of the Costs of Forwarding Contracts with Machine Learning Methods
Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 413–416 (2022)
Abstract. This paper summarizes conducted experiments andfindings related to FedCSIS 2022 Challenge that we participated in. The task was to develop a predictive model that estimated costs pertained to the execution of forwarding contracts (FC). We thoroughly analyze the dataset and present steps performed in the data preprocessing stage. Then we describe our approach to building a predictive model, which placed us eighth out of 135 teams. In the end, a wide range of ideas for further research is provided.
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