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Mar 28, 2024
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DAT 330 - Data Mining This course will introduce students to data mining and its applications in business and social problems. The course will cover supervised data mining techniques for building prediction models that include decision trees, random
decision forests, training and testing using multi-fold cross validation and using entropy measures for weighting features. It will also cover an unsupervised data mining technique called apriori that is used for discovering
patterns in data and exploring associations between variables. Prerequisites: Complete CSI-270 or CSI-281. Credits: 3
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