Browsing by Author "Mayo, Michael"

Now showing items 6-10 of 64

  • Alternating model trees

    Frank, Eibe; Mayo, Michael; Kramer, Stefan (ACM Press, 2015)
    Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes. In this paper, we propose ...

  • Automatic end-to-end De-identification: Is high accuracy the only metric?

    Yogarajan, Vithya; Pfahringer, Bernhard; Mayo, Michael (2019)
    De-identification of electronic health records (EHR) is a vital step towards advancing health informatics research and maximising the use of available data. It is a two-step process where step one is the identification of ...

  • Automatic species identification of live moths

    Mayo, Michael; Watson, Anna T. (Elsevier Science Publishers B.V., 2007)
    A collection consisting of the images of 774 live moth individuals, each moth belonging to one of 35 different UK species, was analysed to determine if data mining techniques could be used effectively for automatic species ...

  • Bayesian sequence learning for predicting protein cleavage points

    Mayo, Michael (Springer, 2005)
    A challenging problem in data mining is the application of efficient techniques to automatically annotate the vast databases of biological sequence data. This paper describes one such application in this area, to the ...

  • BlockCopy-based operators for evolving efficient wind farm layouts

    Mayo, Michael; Zheng, Chen (IEEE, 2016)
    A novel search operator, BlockCopy, is proposed for efficiently solving the wind farm layout optimisation problem. BlockCopy, which can be used either as mutation or a crossover operator, copies patterns of turbines from ...