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May 12, 2024
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2023-2024 Graduate Catalog
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BIA 6301 - Applied Data Mining
(2)
Applied Data Mining introduces students to supervised and unsupervised machine learning methods. Supervised methods include linear regression, logistic regression, k-nearest neighbor, Naïve Bayes, and decision trees. Unsupervised methods include cluster analysis and association rules. Data preparation, dimension reduction, and model performance evaluation are also examined. Emphasis is placed on working with large data sets in business context and communicating results to diverse audiences. The primary software used is R but other tools may be incorporated.
Prerequisite: BIA 6201 , BIA 6202 , and BIA 6203 , or consent of the Program Director.
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