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Dec 22, 2024
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2020-2021 Graduate Catalog [ARCHIVED CATALOG]
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BIA 6301 - Applied Data Mining
(2)
Applied Data Mining introduces students to supervised and unsupervised learning methods for classification and prediction. This course emphasizes working with large data sets and communicating results to managerial audiences. Supervised methods examined in the course include linear regression, logistic regression, k-nearest neighbor, Naïve Bayes, and decision trees. Unsupervised methods include cluster analysis and association rules. Data preparation and reduction and model performance evaluations are also introduced throughout the course. Students will complete and present a final data mining project using real data.
Prerequisite: BIA 6300 , BIA 6201 , and BIA 6311 or consent of the program director.
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