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Dec 26, 2024
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COSC 526 - Introduction to Data Mining3 Credit Hours
A comprehensive introduction to the field of data mining. Topics covered include data preprocessing, predictive modeling (e.g., decision trees, SVM, Bayes, K-nearest neighbors, bagging, boosting), model evaluation techniques, clustering (hierarchical, partitional, density-based), classification, association analysis, and anomaly detection. Case studies from text mining, electronic commerce, social science, and bioinformatics are covered. All programming projects are student-designed (no standard packages permitted).
Recommended Background: Programming proficiency in languages such as C, C++, or Java. Knowledge of scripting languages such as Perl or Python is very beneficial.
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