Feature Selection Methods for Classification in Machine Learning

Using machine learning feature selection methods for classification purposes. Methods used will be: Forward Stepwise Logistic Regression, LASSO logistic regression, the C5.0 decision tree, Rpart Decision trees, and CHAID decision trees. Learning to use multiple methods to create interpretable classifiers. Also, simple bootstrapping and cross-fold validation methods will be implemented.

This talk is contributed by Brendan Cord Lethebe (Biostatistician, Clinical Research Unit, University of Calgary). I would like to acknolwedge his contribution for our group. Everyone is welcome! More information can be found at "http://people.ucalgary.ca/~chelhee.lee/pages/crug.html"

This event is supported by the Pacific Institute for the Mathematical Sciences.

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