We had 5 teams, all of them having submitted an amazing contribution to Explainers for the proposed Task and promising reusability of their implemented methods. Congratulations !
Top 1 : Indiana Team with Zachary W., David L and David C. Leveraging SHAP and CBR for Dimensionality Reduction on the Psychology Prediction Dataset
Top 2 : Aberdeen Scool of Computing team with Craig P., Malavika S., Pedram S., Chamath P., Gayani N. Explainable Weather Forecasts Through an LSTM-CBR Twin System
Top 3: Nordic team with Betul B., Paola M., Kerstin B. Explaining your Neighbourhood: A CBR Approach for Explaining Black-Box Models
and prize 4 to CBR-FOX AAIMX team Fernando V., Gerardo P.,
Humberto S., Carlos S., Mauricio O. CBR-foX:A generic post-hoc case-based reasoning method for the explanation of time-series forecasting
prize 5 to IREX AAIMX team Cristian S., Manuel C., Jose S., Jesus D., Esteban B., Nora C., Mauricio O. A reusable process for the iterative refinement and explanation of classification models
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