Question: Cross-Validation refers to the practice of creating a model using part of the data as a training set of data and then testing the model

Cross-Validation refers to the practice of creating a model using part of the data as a training set of data and then testing the model on the remaining data from the dataset, then reversing the roles of the two datasets (train becomes test and test becomes train).

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