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I have made regression selecting the best features (p-val<0.05). I now have the model with a 0.85 R-squared and residual of 2.64.
Well, sometimes when I try to predict some new instances, my predictions is way outside my residual deviation. I mean sometime my actual y-value is supposed to be 20 and I have 26,7.
I also fell the need to mention that when I explored my target with a boxplot; I had a maximum of 33 and outliers going up to 100 and the standard deviation for that target is nearly 7.
The good thing is, I have over a million of rows and the outliers represent about 5000 rows. Is taking them off improve my model? what can I do to improve such a model?

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