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  • Explanatory approach for evaluation of machine learning-induced knowledge
    Zorman, Milan ; Verlič, Mateja
    Progress in biomedical research has resulted in an explosive growth of data. Use of the world wide web for sharing data has opened up possibilities for exhaustive data mining analysis. Symbolic ... machine learning approaches used in data mining, especially ensemble approaches, produce large sets of patterns that need to be evaluated. Manual evaluation of all patterns by a human expertis almost impossible. We propose a new approach to the evaluation of machine learning-induced knowledge by introducing a pre-evaluation step. Pre-evaluation is the automatic evaluation of patterns obtained from the data mining phase, using text mining techniques and sentiment analysis. It is used as a filter for patterns according to the support found in online resources, such as publicly-available repositories of scientific papers and reports related to the problem. The domain expert can then more easily distinguish between patterns or rules that are potential candidates for new knowledge.
    Source: Journal of international medical research. - ISSN 0300-0605 (Letn. 37, št. 5, 2009, str. 1543-1551)
    Type of material - article, component part
    Publish date - 2009
    Language - english
    COBISS.SI-ID - 13645334

source: Journal of international medical research. - ISSN 0300-0605 (Letn. 37, št. 5, 2009, str. 1543-1551)

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