A learning algorithm is typically applied at two distinct times. Training time refers to the time when an algorithm is learning a model from training data. Test time refers to the time when an algorithm is applying a learned model to make predictions. Lazy learning usually blurs the distinction between these two times, deferring most learning until test time.
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(2017). Training Time. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_975
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