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Browsing by Subject "Supervised learning"

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  • Barnard, E (PRASA, 2009-11)
    The authors have previously argued that the infamous "No Free Lunch" theorem for supervised learning is a paradoxical result of a misleading choice of prior probabilities. Here, they provide more analysis of the dangers ...
  • Twala, B; Phorah, M (Elsevier, 2010-10)
    With the wealth of sequence data and the huge amount of data generated from molecular technologies, the issue of gene classification/prediction has become a central challenge in the field of microarray data analysis. This ...