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Lessons Learned from Data Mining Challenges



It becomes a good habit to organize a data mining cup, a competition or a challenge at machine learning or data mining conferences. Such events can be used for comparison of various approaches and algorithms, they give the participants a possibility to access and analyze real-world data, and they can result in knowledge interesting for the domain experts who provided the data. Cups and competitions are usually organized around a well-defined classification problem whereas challenges do not have a clear specification what to look for. The paper describes our experience gained when organizing and evaluating the data mining challenges during European Conferences on Data Mining and Machine Learning. It shows the challenge settings, describes the used data and the solved tasks and summarizes the lessons learned.


Data Mining, Machine Learning, Classification, Prediction, Knowledge Acquisition, Discovery Challenge.
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