Train/Test

The data is generally divided into training data to train models and test data to evaluate them. sklearn.model_selection.train_test_split performs this division randomly with a certain proportion, e.g. 80 percent of training and 20 percent of testing. The random_state argument makes the division reproducible in every experiment. Valid evaluation is only possible if the model is evaluated on data that was never used during training.