Solved – 10-fold cross validation or hold out method

I am trying to construct a rule-based classifier on a dataset with 332 instances and 14 features. I am just confused how can I validate the classification model? 10-fold cross validation or holdout method should be used?

Can I just apply the 10-fold cross validation for validation or the model has to be tested by a different set?

Holdout is essentially a 2-fold cross validation. If you perform k-fold cross validation correctly, no extra holdout set is necessary.

Make sure that your predictors are chosen based on the test sets (and not in advance on all the samples). You may also want to think about stratification if appropriate.

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