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Hybrid machine learning: Myth and reality

Moustakis Vasilis, Gavriel Salvendy

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/B58E2B20-7AFA-4551-9FF8-4AF8AF51A353
Έτος 1995
Τύπος Σύντομη Δημοσίευση σε Συνέδριο
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά 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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Περίληψη

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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