Update README.md

README.md

@@ -107,13 +107,19 @@ We trained baseline classifiers using the enriched dataset:
   - F1 (spam): ~0.92
 
   Logistic Regression Report (Combined Features):
+
+  
               precision    recall  f1-score   support
 
            0       0.99      1.00      0.99       904
            1       0.98      0.92      0.95       131
 
     accuracy                           0.99      1035
+
+  
    macro avg       0.99      0.96      0.97      1035
+
+  
 weighted avg       0.99      0.99      0.99      1035
 
 
@@ -124,7 +130,9 @@ Random Forest Report (Combined Features):
            1       0.99      0.86      0.92       131
 
     accuracy                           0.98      1035
+    
    macro avg       0.99      0.93      0.96      1035
+   
 weighted avg       0.98      0.98      0.98      1035
 
 ---
@@ -144,6 +152,7 @@ If you use this dataset, please cite the original SMS Spam Collection dataset:
 
 > @inproceedings{Almeida2011SpamFiltering, title={Contributions to the Study of SMS Spam Filtering: New Collection and Results}, author={Tiago A. Almeida and Jose Maria Gomez Hidalgo and Akebo Yamakami}, year={2011}, booktitle = "Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11)", }.  
 
+> Dataset Enrichment and Feature Engineering contributions by Naga Adithya Kaushik (GenAIDevTOProd). 
 ---
 
 ## License