# Why there is very large difference between cross validation scores?

I have a very simple regression model and I am doing the cross validation. When cv=10 the highest score i got is 60.3 and lowest is -9.7 which is useless. Average will be 30.

No of row data set= 658

• What do you mean by cross-validation scores ? – Subhash C. Davar Mar 17 at 14:23

Your $$R^2$$ scores indicate that a linear model does not describe your data well. On top of this, there seems to be a large variability in data. You could try the following:
• Introducing regularization (lasso or ridge regression) might make the model more robust. This should decrease the variability of the CV errors, but the $$R^2$$ scores will get even worse.