STAT 6386 Statistical Data Mining
This course will provide the necessary statistical knowledge required for the effective handling of data mining techniques. The topics include an introduction to statistical learning, probability distributions, linear models for regression, linear models 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 applications from various interdisciplinary fields to discover hidden patterns and to make efficient predictions. R software will be used for the computational analysis.
Offered
As scheduled