MATH 6386 Statistical Data Mining

This course will provide the necessary statistical knowledge requires for an effective handling of data mining techniques. The topics include; Introduction to statistical learning, probability distributions, linear models for regression, linear model for classifications (linear discriminant analysis, logistic regression), artificial neural networks, support vector machine, resampling and regularization methods, variable selection, dimension reduction and clustering. Students will be given the opportunity to apply data mining techniques to real-world application from various interdisciplinary fields to discover the hidden patterns and to make efficient predictions. R software will be used for the computational analysis.

Credits

3

Prerequisite

MATH 6360 and MATH 6364