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+++ b/README.md
@@ -19,3 +19,10 @@ A summarized version of the results has been included in a graph titled "Feature
 ![Feature Importance.png](https://github.uconn.edu/tjb19003/3504-honors-conversion/blob/main/Feature%20Importance.png?raw=true)
 
 Furthermore, the random forest model generated using this data had a model score of ~0.6258 and a mean squared error of 4.133.
+
+## REFERENCES:
+
+- https://pandas.pydata.org/pandas-docs/version/1.5/index.html
+- https://realpython.com/pandas-dataframe/
+- https://github.com/afrozchakure/Internity-Summer-Internship-Work/blob/master/Blogs/Random_Forest_Classification/Random%20Forest%20Classifcation.ipynb
+- https://scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html