# Technical details

## Supported models

- Linear Regression, Logistic Regression
- Random Forest
- Decision Tree
- Gradient Boosting
- XGBoost
- Dense Neural Network

## Supported explaination methods


- LIME
- Integrated Gradients
- Saliency
- DeepLift
- InputXGradient
- FeatureAblation
- ShapleyValueSampling
- KernelShap

## Evaluation metrics

- Robustness: Sensitivity
- Faithfulness: Infidelity, Comprehensiveness, Sufficiency, Faithfulness Correlation, AUC-TP, Monotony
- Complexity: Complexity, Sparseness

More details can be found in [this page](metrics.md).