Browsing by Author "Vanschoren, Joaquin"

Now showing items 6-10 of 10

  • Learning from the past with experiment databases

    Vanschoren, Joaquin; Pfahringer, Bernhard; Holmes, Geoffrey (University of Waikato, Department of Computer Science, 2008-06-24)
    Thousands of Machine Learning research papers contain experimental comparisons that usually have been conducted with a single focus of interest, and detailed results are usually lost after publication. Once past experiments ...
  • The online performance estimation framework: heterogeneous ensemble learning for data streams

    van Rijn, Jan N.; Holmes, Geoffrey; Pfahringer, Bernhard; Vanschoren, Joaquin (Springer, 2018)
    Ensembles of classifiers are among the best performing classifiers available in many data mining applications, including the mining of data streams. Rather than training one classifier, multiple classifiers are trained, ...
  • Organizing the World’s Machine Learning Information

    Vanschoren, Joaquin; Blockeel, Hendrik; Pfahringer, Bernhard; Holmes, Geoffrey (Springer, 2009)
    All around the globe, thousands of learning experiments are being executed on a daily basis, only to be discarded after interpretation. Yet, the information contained in these experiments might have uses beyond their ...
  • Scientific workflow management with ADAMS

    Reutemann, Peter; Vanschoren, Joaquin (Springer, 2012)
    We demonstrate the Advanced Data mining And Machine learning System (ADAMS), a novel workflow engine designed for rapid prototyping and maintenance of complex knowledge workflows. ADAMS does not require the user to manually ...
  • Towards Meta-learning over Data Streams

    van Rijn, Jan N.; Holmes, Geoffrey; Pfahringer, Bernhard; Vanschoren, Joaquin (CEUR-WS, 2014)
    Modern society produces vast streams of data. Many stream mining algorithms have been developed to capture general trends in these streams, and make predictions for future observations, but relatively little is known about ...