Machine Learning with R Cookbook - Second Edition

How it works...

The measurement of the performance of the regression model employs the distance between the predicted value and the actual value. We often use these three measurements, root mean square error, relative square error, and R-Square, as the quantifier for the performance of regression models. In this recipe, we first load the Quartet data from the car package. We then use the lm function to fit the linear model, and add the regression line on a scatter plot of the x variable against the y3 variable. Next, we compute the predicted value using the predict function, and begin to compute the Root Mean Square Error (RMSE), Relative Square Error (RSE), and R-Square for the built model.

As this dataset has an outlier at x=13, we would ...