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- W3033200972 abstract "Data is currently one of the most critical and influential emerging assets. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data is ever actually analyzed for value creation [1]. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen's framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application." @default.
- W3033200972 created "2020-06-12" @default.
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- W3033200972 creator A5069519801 @default.
- W3033200972 date "2020-01-15" @default.
- W3033200972 modified "2023-09-27" @default.
- W3033200972 title "A Machine Learning Decision Support Framework for Industrial Engineering Purposes" @default.
- W3033200972 cites W2012533078 @default.
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- W3033200972 doi "https://doi.org/10.1145/3394941.3394943" @default.
- W3033200972 hasPublicationYear "2020" @default.
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