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subtitle: "Split data into training (to fit) and test (to evaluate prediction)"
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Data is often split so that \~20% of the observations (presence and absence) are set aside from the model fitting to be used for model evaluation.
The `k-fold` function is often used to split the data into k groups, and then the model is fit k times, each time using a different group as the test data and the remaining groups as the training data.