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Bibliographic content of Data Mining: Foundations and Practice. S. P. Subasingha, J. Zhang, Kamal Premaratne, Mei-Ling Shyu, Miroslav Kubat, K. K. Rohitha Hewawasam: Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method.
Page 1 of 5 Data Mining Practice Final Exam Solutions Note: This practice exam only includes questions for material after midterm—midterm exam
Tsau Young Lin, Ying Xie, Anita Wasilewska and Churn-Jung Liau (Eds.) Data Mining: Foundations and Practice Studies in Computational Intelligence, Volume 118 Editor-in-chief Prof. Janusz Kacprzyk Systems Research Institute Polish Academy of Sciences ul.
Data mining is a framework for collecting, searching, and filtering raw data in a systematic matter, ensuring you have clean data from the start. It also helps you parse large data sets, and get at the most meaningful, useful information.

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