How to do k-fold validation with classifiers? I want to cross-validate a model that plays the card game below (see image).

I trained the model on a dataset of 1000 games, with the goal to maximise the profit of each game. It works great on the training dataset, but I want to k-fold validate it, to ensure that it generalises well.

How can I apply k-fold validation in this case?. This model is not a regressor. It is a classifier, with a variable reward/penalty moreover. So I cannot calculate the MSE of validation folds, there is no MSE here. How can I apply k-fold validation in this case?
So I cannot calculate the MSE of validation folds, there is no MSE
  here.


The question that you firstly need to ask is "how do I evaluate my model".

Since the model is a classifier, you can use the accuracy (number of correct classifications over the overall attempts) or the F-score as measures of your model's performance. Based on the chosen measure, you will thereafter evaluate the results of kfold-validation.