Comparing the results of classifiers

We have created around six classification models on the HR attrition dataset. The following table summarizes the evaluation scores for each model:

The random forest model appears to be a winner among all six models, with a record-breaking 99% accuracy. Now, we need not further improve the random forest model, but check whether it can generalize well to a new dataset and the results are not overfitting the train dataset. One of the methods is to do cross-validation.