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Proceedings of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 30

Predicting the Costs of Forwarding Contracts: Analysis of Data Mining Competition Results

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DOI: http://dx.doi.org/10.15439/2022F303

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 399–402 ()

Full text

Abstract. We describe an international data mining competition FedCSIS 2022 Challenge: Predicting the Costs of Forwarding Contracts that was organized in association with the FedCSIS conference series at the KnowledgePit platform. We explain the competition scope and briefly discuss the results obtained by the most successful teams. We also share the most interesting findings of our post-competition research assisted by the BrightBox technology, and describe our own prediction model that was used as the competition baseline. Finally, we show the results of our experiment conducted with the solution ensembling mechanism provided by KnowledgePit. The goal of this experiment was to find a mixture of submitted predictions that is the most accurate estimation of real execution costs of forwarding contracts.

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