The examples use data from standard machine learning libraries to demonstrate how forestci can be used to calculate error bars on RandomForestRegressor and 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.

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