Cross-validation in brief

For the various values of \( k \)

1. shuffle the dataset randomly.
2. Split the dataset into \( k \) groups.
3. For each unique group:
   1. Decide which group to use as set for test data
   2. Take the remaining groups as a training data set
   3. Fit a model on the training set and evaluate it on the test set
   4. Retain the evaluation score and discard the model
4. Summarize the model using the sample of model evaluation scores

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