This chapter covers the following topics:
Fitting a linear regression model with
lm
Summarizing linear model fits
Using linear regression to predict unknown values
Measuring the performance of the regression model
Performing a multiple regression analysis
Selecting the best-fitted regression model with stepwise regression
Applying the Gaussian model for generalized linear regression
Performing a logistic regression analysis
Building a classification model with recursive partitioning trees
Visualizing a recursive partitioning tree
Measuring model performance with a confusion matrix
Measuring prediction performance using
ROCR