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COunterfactual explanations with Limited Actions (COLA)
COunterfactual explanations with Limited Actions (COLA)
Traditional counterfactual explainers often produce explanations that require changing many features. COLA refines these explanations to be more actionable:
✅ 30-50% fewer actions compared to raw counterfactuals
✅ Works with different ML models (sklearn, PyTorch)
✅ Built-in Counterfactual explainers (DiCE, DisCount)
✅ Compatible with all generated counterfactuals (in DataFrame format)
✅ Theoretically grounded - based on joint-distribution-informed Shapley values (see our paper)
✅ Easy to use - simple API with sensible defaults
✅ Rich visualizations - heatmaps, charts, highlighted tables
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