There are a lot of data mining algorithms and methodologies for various fields and various problematic. Each data mining researcher/practitioner is faced with assessing the performance of his own solution(s) in order to make comparisons with state of the art approaches. He should also describe the intrinsic quality of the discovered patterns. Which methodology, which benchmarks, which measures of performance, which tools, which measures of interest, etc., should be used, and why? Every one should answer the previous questions, and assessing the quality and the performance is a critical issue.
This blog is dedicated to discussions about such issues in data mining.
In particular, it can be an excellent forum to prepare The second Quality issues, measures of interestingness and evaluation of data mining models workshop (QIMIE'11) organized in association with the next PAKDD'11 conference (15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Shenzhen, China, May 24-27, 2011), a major international conference in the areas of data mining and knowledge discovery.
Philippe & Stéphane