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Browsing College of Health and Human Services by Subject "AQ learning"

Browsing College of Health and Human Services by Subject "AQ learning"

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  • Kaufman, Kenneth A.; Michalski, Ryszard S. (2000-03)
    In concept learning and data mining tasks, the learner is typically faced with a choice of many possible hypotheses or patterns characterizing the input data. If one can assume that training data contain no noise, then ...
  • Michalski, Ryszard S. (2004-12)
    In many areas of application of machine learning and data mining, it is desirable to generate alternative inductive hypotheses from the given data. The Aq-ALT or, briefly, ALT method, presented in this paper, generates ...
  • Cervone, Guido; Michalski, Ryszard S. (2002-06)
    The paper describes recent results from developing and testing LUS methodology for user modeling. LUS employs AQ learning for automatically creating user models from datasets representing activities of computer users. The ...
  • Wojtusiak, Janusz; Michalski, Ryszard S.; Kaufman, Kenneth A.; Pietrzykowski, Jaroslaw (2006-06)
    The AQ21 program seeks different types of patterns in data and represents them in human-oriented forms resembling natural language descriptions. Because of the latter feature it is called a natural induction program. This ...
  • Michalski, Ryszard S.; Wojtusiak, Janusz (2005-06)
    This paper describes methods for reasoning with missing, irrelevant and not applicable meta-values in the AQ attributional rule learning. The methods address issues of handling these values in datasets both for rule learning ...
  • Michalski, Ryszard S.; Wojtusiak, Janusz (2007-11-18)
    AQ learning strives to perform natural induction that aims at deriving general descriptions from specific data and formulating them in human-oriented forms. Such descriptions are in the forms closely corresponding to simple ...

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