Explainable AI

Feature Attributions

Understanding the Feature Attribution Methods

LIME

Figure 1: (a) LIME explanation for logistic regression model trained on iris dataset and
(b) LIME explanation for linear regression trained on Boston housing dataset.
Figure 2: LIME explanation for BERT model trained on BBC news dataset.
Figure 3: LIME explanation for image classification model on cats and dog dataset.

GradCAM

Figure 4: GradCAM result for VGG16 model trained on human activity recognition dataset.

Deep Taylor

Figure 5: Deep Taylor result for VGG16 model trained on human activity recognition dataset.

SHAP

Figure 6: SHAP result for VGG16 model trained on human activity recognition dataset.
Figure 7: SHAP results for YOLOv3 model trained on the COCO dataset.
Figure 8: (a) SHAP result for text classification using BERT
Figure 8: (b) SHAP result for text summarization using Schleifer/distilbart-cnn-12–6 model.

SODEx

Figure 9: SODEx result for YOLOv3 model trained on the COCO dataset.

SegGradCAM

Figure 10: SegGradCAM result for U-net model trained on camvid dataset.

Conclusion

  1. Selvaraju et al. “Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization.” International Journal of Computer Vision 2019
  2. http://www.heatmapping.org/slides/2018_ICIP_2.pdf
  3. https://towardsdatascience.com/shap-shapley-additive-explanations-5a2a271ed9c3
  4. Sejr, J.H.; Schneider-Kamp, P.; Ayoub, N. Surrogate Object Detection Explainer (SODEx) with YOLOv4 and LIME
  5. https://www.steadforce.com/blog/explainable-object-detection
  6. Vinogradova, K., Dibrov, A., & Myers, G. (2020). Towards Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping

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Affine is a provider of analytics solutions, working with global organizations solving their strategic and day to day business problems www.affineanalytics.com

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Affine is a provider of analytics solutions, working with global organizations solving their strategic and day to day business problems www.affineanalytics.com

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