Update README.md

README.md

@@ -295,31 +295,23 @@ correltions. This indicates that biological markers remain the dominant predicto
 
 ![Feature Correlation](feature_correlation_diabetes.png)
 
-The feature target heatmap reinforce the importance of HbA1c, glucose as the stongest predictors. Age and family history of diabetes also dispaly meaningful correlations,
-indicating they are important risk indicators
-Others varibales display only mild linear realtionship with diabetes diagnoaia
+This heatmap uses spearman correlation, which help detact not-liner monotonic relationships between features and diabetes diagnosis. The results reinforce earlier findings:
+-HbA1c and fasting glucose remain the strongest predictors.
+-Age and family history of diabetes shows meaningful positive correlations.
+lifestyle varibales display only weak monotonic relationships.
 
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-## **9️⃣ Why calculate Spearman correlation as well?**
-
-### Insight
-- Spearman helps detect **non-linear monotonic relationships**.
-- Age, glucose, HbA1c all remain strong positive correlates.
-- Confirms the **robustness** of findings from Pearson.
-
-📈 *(Insert Spearman ranking plot)*
-
----
-
-## **🔟 What is the class balance between diagnosed and non-diagnosed participants?**
+## **9️⃣ What is the class balance between diagnosed and non-diagnosed participants?**
 
 ### Insight
 - 60% diagnosed vs. 40% not diagnosed.
 - This is **not representative of the real population**, but OK for analysis.
 - Important note: in modeling, **accuracy alone would be misleading**.
 
-📈 *(Insert countplot)*
+### **1. Class Balance- Diabetes vs Non-diabetes**
+
+![Diabetes vs Non-diabetes](class_balance_diabetes.png)
 
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