Explainable AI using FOLD-R++

Inspiration

Dr.Gupta's workshop on Explainable AI using FOLD-R++ was interesting and inspired me to work in datasets using the same and understand the insights in detail

What it does

I have implemented FOLD-R++ algorithm over 13 kaggle classification datasets and reported the performance metrics and observations

How we built it

Cloned the public FOLD-R++ repository and updated the dataset.py and main.py accordingly to test different variety of Kaggle classification datasets

Challenges we ran into

• Understanding the rules generated
• Try improving performance metrics
• Finding different variety of datasets

Accomplishments that we're proud of

• Using FOLD-R++ algorithm effectively
• Try the algorithm over variety of data sets

What we learned

• Understand the essence of Explainable AI
• How to derivr more insights from a machine learning model

What's next for Explainable AI using FOLD-R++

• Test the algorithm over regression dataset
• Find areas of more hyperparameter tuning
• Involve more data preprocessing

Built With

• python