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Hybrid machine learning: Myth and reality

Moustakis Vasilis, Gavriel Salvendy

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URI: http://purl.tuc.gr/dl/dias/B58E2B20-7AFA-4551-9FF8-4AF8AF51A353
Year 1995
Type of Item Conference Short Paper
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Bibliographic Citation V. Moustakis and G. Salvendy, "Hybrid Machine Learning: Myth and Reality" in Sixth International Conference on Human Computer Interaction: Symbiosis of Human and Artifact, 1995, pp. 1083 – 1088. doi: 10.1016/S0921-2647(06)80171-1 https://doi.org/10.1016/S0921-2647(06)80171-1
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Summary

An important issue to consider when applying Machine Learning (ML) in a real world task is the selection of a system, algorithm or approach which should be used. In this context coupling of the right ML approach with the task at hand is not trivial. This paper reports the preliminary results of a research which targeted to coupling ML approaches with generic intelligent tasks. Preliminary analysis makes it clear that in most of tasks application of a single ML approach is not satisfactory and that hybrid formations are necessary.

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