How to get a fuller picture of a model's accuracy

Using a single train-test split gives you a single snapshot of the performance of a machine learning model or algorithm. It's like evaluating a football team (American or otherwise) based on a single game. If you really want to know how well a team performs in general, you're going to want more than just this snapshot. Likewise, we shouldn't evaluate our algorithms on a single random split. I bring you k-fold cross validation.