Continuing where I left off last time which was the comparison of different models with their test errors using the K fold cross validation approach.
To start off, I used the simplest linear model with diabetes modeled on inactivity and obesity. Further down the line a complicate the model further by adding interaction terms or square terms on the basis of the tests from yesterday to improve the model fit.
All of these were used to calculate the test error resulting from a K = 10 fold.
As is seen from this, I was achieving my lowest test errors for the log models but I believe there is something further I need to investigate into this because of how much the drop off in error is, when compared to its other simpler models.