In k-fold cross-validation, the original dataset is equally partitioned into k subparts or folds. Out of the k-folds or groups, for each iteration, one group is selected as validation data, and the remaining (k-1) groups are selected as training data. The process is repeated for k times until each group is treated as validation and remaining as training data.

Question: For my research project, I did not do k-fold cross validation iteratively. I took 90% of the data to train my model and 10% to test my model. I did that process only once (in one iteration). What is the name of this technique?