This chapter fits a model to the mtcars dataset, reads its coefficients, and predicts from it. It starts with ordinary least squares, then introduces regularization and fitting from named columns.
1.1.1 Installing
1.1.2 A First Regression
1.1.2.1 Plotting the fit and path
1.1.2.1.1 Predicted versus actual values
1.1.2.1.2 Residuals versus fitted values
1.1.2.1.3 The lasso coefficient path
1.1.3 Fitting from named columns
1.1.4 Choosing a model
1.1.5 Predicting
1.1.6 What is not there yet