Machine Learning, Data Science, Artificial Intelligence.
zero, you are correct. You should be wary whenever your error is zero because nothing is that good. This is called overfitting. To prevent this, we reserve some of our data set so that the model can be tested on points it has not been trained on! Cross validation just means doing this process over