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• W1513016872 abstract "The paper presents the data exploration issue in a context of the prediction tasks solution. There are presented three methodologies of data models construction in the paper. The methodologies are used to solve the prediction tasks. They also deliver an easily interpretable knowledge about the modeled process. The methodologies, called hybrid methods, combine analytical algorithms (clustering, rules induction) and optimization algorithms (genetic algorithms, error backpropagation). The paper presents also a method of a data transformation between the temporal data representation and the data representation acceptable. for algorithms using learning by examples paradigm. The paper presents also the results of the experiments performed on the benchmark data and the data obtained from a methane concentration monitoring system in a coal mine." @default.
• W1513016872 created "2016-06-24" @default.
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• W1513016872 date "2006-04-30" @default.
• W1513016872 modified "2023-09-25" @default.
• W1513016872 title "Hybrid Data Exploration Methods to Prediction Tasks Solving" @default.
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