Data Mining in R

This set of notes for undergraduate and graduate data mining class is currently maintained by Xiaorui Zhu([email protected]). Many materials are from Dr. Yan Yu's previous class notes. And lab notes are from four previous PhD students in Lindner College of Business.

Contributors:
Dr. Shaonan Tian, Associate Professor at San José State University Dr. Chaojiang Wu, Assistant Professor at Kent State University Dr. Feng Mai, Assistant Professor of Information Systems in the School of Business at Stevens Institute of Technology Dr. Shaobo Li, Assistant Professor of Business Analytics at University of Kansas School of Business

Lecture and Lab Notes

R Basic

R Basic

Explore and describe dataset

Explore and describe dataset

Linear Regression, Prediction and Variables Seleciton

Linear Regression

Logistic Regression

Logistic Regression

Tree Models

Regression tree and classification tree

GAM, Neural Network, LDA and SVM

GAM, Neural Network, LDA and SVM

Unsupervised Learning

Unsupervised Learning

Advanced Tree

Advanced Tree Models -- Bagging, Random Forests, and Boosting

Other Topics 2: Advanced Variable Selection

Advanced Variable Selection Techniques