Update README.md

README.md

@@ -14,38 +14,38 @@ mechanism related to the text classification domain.
 
 ## Individual research question
 
-### IT20097660 | Sashini Devindi
+#### IT20097660 | Sashini Devindi
 How to get a counterfactual rule generation-based explanation for the Support Vector Machine classifier, when it handle  
 non-linear separable data in text classification?
 
-### Srinidee
+#### Srinidee
 How to get a counterfactual rule generation-based explanation for the Logistic Regression classifier when it becomes black box 
 in text classification?
 
-### Thilini Anjalika
+#### Thilini Anjalika
 How to get a counterfactual rule generation-based explanation for the Random Forest classifier, when it becomes black box in 
 text classification?
 
-### IT20013950 | Lakshani N.V.M.
+#### IT20013950 | Lakshani N.V.M.
 How to get a counterfactual rule generation-based explanation for the k-NN classifier, when it handle  Curse of Dimensionality 
 problem in text classification?
 
 
 ## Individual Objectives
 
-### IT20097660 | Sashini Devindi
+#### IT20097660 | Sashini Devindi
 Provide a novel post-hoc ,model-specific, local  XAI solution to enhance the model interpretability of function-based 
 classification models focus on  SVM by developing a novel counterfactual rule generation mechanism related to the text 
 classification domain.
 
-### Srinidee
+#### Srinidee
 Providing model specific ,local ,post-hoc explanations using counterfactual mechanisms to improve the interpretability of the system.
 
-### Thilini Anjalika
+#### Thilini Anjalika
 Provide a novel post-hoc ,model-specific, local  XAI solution to enhance the model interpretability of ensemble models focus 
 on  Random forest by developing a novel counterfactual rule generation mechanism related to the text classification domain.
 
-### IT20013950 | Lakshani N.V.M.
+#### IT20013950 | Lakshani N.V.M.
 Provide a novel post-hoc ,model-specific, local  XAI solution to enhance the model interpretability of distance-based classification 
 models focus on  k-NN by developing a novel counterfactual rule generation mechanism related to the text classification domain.