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• Data mining is a generally well-founded practical disciplinethat aims to identify interesting new relationships and patterns from data (but it is broader than that). • This course is designed to introduce basic and some advanced concepts of data mining and provide hands-on experience to data analysis, clustering, and prediction.
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Li Zheng, Chao Shen, Liang Tang, Tao Li, Steve Luis, Shu-Ching Chen, Vagelis Hristidis, Using data mining techniques to address critical information exchange needs in disaster affected public-private networks, Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, July 25-28, 2010, Washington ...
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Data Mining. Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach and Vipin Kumar Lecture slides (in both PPT and PDF formats) and three sample Chapters on classification, association and clustering available at the above link. Data Mining - Concepts and Techniques (3rd edition) by Jiawei Han, Micheline Kamber & Jian Pei
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Feb 14, 2018· Avoiding False Discoveries: A completely new addition in the second edition is a chapter on how to avoid false discoveries and produce valid results, which is novel among other contemporary textbooks on data mining. It supplements the discussions in the other chapters with a discussion of the statistical concepts (statistical significance, p-values, false discovery rate, permutation testing ...
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