Best Paper Award ECMLPKDD 2014

  • Reliability maps: A tool to enhance probability estimates and improve classification accuracy (Meelis Kull, Peter Flach)

Best Student Paper Award ECMLPKDD 2014

  • Discovering dynamic communities in interaction networks (Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis)

  • Statistical Hypothesis Testing in Positive Unlabelled Data (Konstantinos Sechidis, Borja Calvo, Gavin Brown)


    Konstantinos Sechidis, University of Manchester
    Borja Calvo, University of the Basque Country
    Gavin Brown, University Of Manchester


    We propose a set of novel methodologies which enable valid statistical hypothesis testing when we have only positive and unlabelled (PU) examples. This type of problem, a special case of semi-supervised data, is common in text mining, bioinformatics, and computer vision. Focusing on a generalised likelihood ratio test, we have 3 key contributions: (1) a proof that assuming all unlabelled examples are negative cases is sufficient for independence testing, but not for power analysis activities; (2) a new methodology that compensates this and enables power analysis, allowing sample size determination for observing an effect with a desired power; and finally, (3) a new capability, supervision determination, which can determine a-priori the number of labelled examples the user must collect before being able to observe a desired statistical effect. Beyond general hypothesis testing, we suggest the tools will additionally be useful for information theoretic feature selection, and Bayesian Network structure learning.

Test of Time Award ECMLPKDD 2014

  • Applying Support Vector Machines to Imbalanced Datasets (Rehan Akbani, Stephen Kwek, Nathalie Japkowicz)