Machine Learning with R Cookbook - Second Edition

How it works...

We first build a linear fitted model with x and y1 variables. Next, we assign values to be predicted into a DataFrame, newdata. It is important to note that the generated model is in the form of y1 ~ x.

Next, we compute the prediction result using a confidence interval by specifying confidence in the argument interval. From the output of row 1, we get fitted y1 of the x=3 input, which equals to 4.500364, and a 95 percent confidence interval (set 0.95 in the level argument) of the y1 mean for x=3 is between 2.691375 and 6.309352. In addition to this, row 2 and 3 give the prediction result of y1 with an input of x=6 and x=15.

Next, we compute the prediction result using a prediction interval by specifying prediction in the argument ...