Query-By-Multiple-Examples using Support Vector Machines (Supplement)

• SVM-perf 2.10 extended with the loss function options precision-recall product (-l 21) and balanced accuracy (-l 22): [.tar.gz]
• Please refer to Thorsten Joachims's SVM-perf website.

• news20
• siam-competition2007
• mediamill-exp1
• reuters-21578

• Charles Elkan and Keith Noto. Learning Classifiers from Only Positive and Unlabeled Data. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Las Vegas, NV, USA, Aug 2008. [paper] [data]
• Dell Zhang, Wee Sun Lee. A Simple Probabilistic Approach to Learning from Positive and Unlabeled Examples. In Proceedings of the 5th Annual UK Workshop on Computational Intelligence (UKCI), London, UK, Sep 2005. [paper]
• Bing Liu. Web Data Mining: Exploring Hyperlinks, Contents and Usage Data, Chapter 5. Springer, 2006.