2020년 12월 29일

Statistical Data Mining (IMEN 472)

Course Objectives:

 This course will cover theories and applications of basic (statistical) data mining techniques including regression, classification and unsupervised learning.

Textbook

1) Hastie, T., Tibshirani, R. and Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. (2nd edition). Springer.

2) James, G., Witten, D., Hastie, T. and Tibshirani, R. (2013). An Introduction to Statistical Learning: with Applications in R. Springer.

 

 

Supplement

[Linear Algebra]

[Multivariate Normal Distribution]

[Conditional Expectation]

 

Materials

[Chapter 1]  – Introduction

[Chapter 2] – Overview of Supervised Learning

[Chapter 3] – Linear Methods for Regression(Part I)

[Chapter 3] – Linear Methods for Regression(Part II)

[Chapter 4] – Linear Methods for Classification

[Chapter 5] – Nonparametric Methods for Regression and Classification