Implement Explainable AI for 'Linear regression' over existing and new models.

[hemantkshirsagar8]

Task.

• Implement Explainable AI for 'Linear regression' over existing and new models.
• Can take any sample use case data from Scikit-learn examples.
• Features need to be self-explanatory during model predictions.
• Bind model in ML pipeline using MLFlow.

[hemantkshirsagar8]

Hows the progress, any difficulties?

[sathish2379]

good so far sir but I am unable to connect to google colab

[hemantkshirsagar8]

Thanks, Satish, Are there any specific issues you're facing for google colab?.

You can paste error here, for more information.

[sathish2379]

sure sir,I will do right now,I am trying to replicate some examples of linear regression

[hemantkshirsagar8]

• Taken diabetes example from sci-kit learn
• Implementation in progress along with SHAP.
• Will be integrating SHAP up to this weekend.
• Deadline accepted - for This Weekend (20th Oct).

[sathish2379]

Here is an example of linear logistic regression along with SHAP refer: https://slundberg.github.io/shap/notebooks/linear_explainer/Sentiment%20Analysis%20with%20Logistic%20Regression.html

[sathish2379]

Successfully integrated SHAP for the diabetes example Have to understand some of the things currently undergoing it

[hemantkshirsagar8]

Any progress on this?