R-squared can help you answer the question "How does my model perform, compared to a naive model?". However, r² is far from a perfect tool. Probably the main issue is that every data set contains a certain amount of unexplainable data. R-squared can't tell the difference between the explainable and the…

R-squared measures how well your data fits a regression line. More specifically, it's how much variation in the…

Cross Validation explained in one simple picture. The method shown here is k-fold cross validation, where data is split into k folds (in this example, 5 folds). Blue balls represent training data; 1/k (i.e. 1/5) balls are held back for model testing.

Monte Carlo cross validation works the same way, except that the balls would be chosen with replacement. In other words, it would be possible for a ball to appear in more than one sample.…