Browsing by Author "Bouckaert, Remco R."

Now showing items 6-10 of 13

  • Estimating replicability of classifier learning experiments

    Bouckaert, Remco R. (ACM, 2004)
    Replicability of machine learning experiments measures how likely it is that the outcome of one experiment is repeated when performed with a different randomization of the data. In this paper, we present an estimator of ...
  • Evaluating the replicability of significance tests for comparing learning algorithms

    Bouckaert, Remco R.; Frank, Eibe (Springer, 2004)
    Empirical research in learning algorithms for classification tasks generally requires the use of significance tests. The quality of a test is typically judged on Type I error (how often the test indicates a difference when ...
  • A hierarchical face recognition algorithm

    Bouckaert, Remco R. (Springer, 2009)
    In this paper, we propose a hierarchical method for face recognition where base classifiers are defined to make predictions based on various different principles and classifications are combined into a single prediction. ...
  • Naïve Bayes for text classification with unbalanced classes

    Frank, Eibe; Bouckaert, Remco R. (Springer, Berlin, 2006)
    Multinomial naive Bayes (MNB) is a popular method for document classification due to its computational efficiency and relatively good predictive performance. It has recently been established that predictive performance can ...
  • Practical bias variance decomposition

    Bouckaert, Remco R. (Springer, 2008)
    Bias variance decomposition for classifiers is a useful tool in understanding classifier behavior. Unfortunately, the literature does not provide consistent guidelines on how to apply a bias variance decomposition. This ...