@@ -15,39 +15,31 @@ mechanism related to the text classification domain.
## Individual research question
- #### 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?
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?
- #### IT18161298 | Srinidee
How to get a counterfactual rule generation-based explanation for the Logistic Regression classifier when it becomes black box
in text classification?
How to get a counterfactual rule generation-based explanation for the Logistic Regression classifier when it becomes black box in text classification?
- #### IT20100698 | Thilini Anjalika
How to get a counterfactual rule generation-based explanation for the Random Forest classifier, when it becomes black box in
text classification?
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.
How to get a counterfactual rule generation-based explanation for the k-NN classifier, when it handle Curse of Dimensionality
problem in text classification?
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
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.
- #### 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.
#### IT18161298 | Srinidee
-#### IT18161298 | Srinidee
Providing model specific ,local ,post-hoc explanations using counterfactual mechanisms to improve the interpretability of the system.
#### IT20100698 | 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.
- #### IT20100698 | 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.
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.
- #### 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.
