# cm012 - November 1, 2017

## Overview

• Demonstrate the use of logistic regression for classification
• Identify methods for assessing classification model accuracy
• Define a decision tree
• Demonstrate how to estimate a decision tree
• Define and estimate a random forest
• Introduce the caret package for statistical learning in R

## Before class

• Read chapters 4.1-3, 8.1, 8.2.2 in An Introduction to Statistical Learning if you want a rigorous introduction to the mathematics behind logistic regression, decision trees, and random forests. In class we will briefly summarize how these methods work and spend the bulk of our time on estimating and interpreting these models