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Author: randleon

Linear-Regression-Using-Sklearn-in-Python.ipynb

@@ -2710,7 +2710,7 @@
    "source": [
     "Interestingly enough, we are presented with an average cross-validated R^2 score of 0.9280 which is our best score yet for our linear regression.\n",
     "\n",
-    "Perhaps this goes back to the more information the better, perhaps if we had more continous variables in our dataset to run linear regression on, we would achieve a higher score.\n",
+    "Perhaps this goes back to the more information the better, perhaps if we had more continous variables in our dataset to run linear regression on, we would achieve a higher score. Granted, I think these results are satisfactory, and perhaps a stronger model could be argued to be overfit.\n",
     "\n",
     "The difference between using our strongest three variables and all of them is not that much, approximately .01 of a difference. This probably alludes to our future lesson of feature selection, showing how only our top three variables were needed for a decent regression."
    ]