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- W2742405931 abstract "A choice of the best computational solution for a particular task is increasingly reliant on experimentation. Even though experiments are often described through text, tables, and figures, their descriptions are often incomplete or confusing. Thus, researchers often have to perform lengthy web searches for reproducing and understanding the results. In order to minimize this gap, vocabularies and ontologies have been proposed for representing data mining and machine learning (ML) experiments. However, we still lack proper tools to export properly these metadata. To this end, we present an open-source library dubbed LOG4MEX which aims at supporting the scientific community to fulfill this gap." @default.
- W2742405931 created "2017-08-17" @default.
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- W2742405931 date "2017-08-23" @default.
- W2742405931 modified "2023-10-01" @default.
- W2742405931 title "LOG4MEX" @default.
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- W2742405931 doi "https://doi.org/10.1145/3106426.3106530" @default.
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