The examples use data from standard machine learning libraries to demonstrate
how forestci can be used to calculate error bars on
RandomForestClassifier objects. The
regression example uses a data-set from the UC Irvine Machine Learning Repository with features of
different cars and their MPG. The classification example generates synthetic
data to simulate a task like that of a spam filter: classifying items into one
of two categories (e.g., spam/non-spam) based on a number of features.