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To Avoid Overfitting Data, What Should be my Rule of Thumb for the Number of Data Points per Variable?
I am currently conducting some regression analysis to predict sales, and I currently have about 45 data points and have collected a lot of potential predictor variables. However, I am weary that I will overfit the data, so I'm wondering...is there a rule of thumb as to how many variables can be assigned given a number of data points, without danger of over-fitting the data? Thanks!
1 Answer
- AmnesiacLv 61 decade agoFavorite Answer
Adjusted R^2 is a really useful tool in this situation. It is very similar to R^2 of simple OLS regressions, but it punishes the excessive use of predictor variables:
