Cross Validation
In last week’s article, I wrote about train-test splits. However, there is a problem with separating the data into only two splits. Since we create random samples of data, the test and train performances can be very different depending on our train-test split. We must validate our model more than one time. We use K-Fold Cross Validation technique to deal with this issue.
