Advanced Machine Learning with R

Training and testing datasets

Here, we are going to put the numeric features into a dataframe along with the quantitative response. Then, we'll carve this up into train and test sets with an 80/20 split. As a closing effort, we'll scale the data, which is required for PCA.

Here, I grab those input features, including height in inches, while dropping weight in kilograms. I also include the subjectid:

> army_subset <- armyClean[, c(1:91, 93, 94, 106, 107)]

We've used the dplyr and caret packages to create train and test sets, and here I demonstrate the dplyr method:

> set.seed(1812)> army_subset %>%    dplyr::sample_frac(.8) -> train> army_subset %>%    dplyr::anti_join(train, by = "subjectid") -> test

I mentioned previously that this data had a ...