Gallery

Model Abstraction

InMemory Model

1. https://github.com/datascienceinc/Skater/blob/master/examples/ensemble_model.ipynb
2. https://github.com/datascienceinc/Skater/blob/master/examples/image_interpretation_example.ipynb
3. https://github.com/datascienceinc/Skater/blob/master/examples/credit_analysis/Credit_Analysis.ipynb

Deployed Model

1. python deployed model: https://github.com/datascienceinc/Skater/tree/master/examples/python-deployed-model
2. r deployed model: https://github.com/datascienceinc/Skater/tree/master/examples/r/deployed_model
3. pre-trained/canned model: https://github.com/datascienceinc/Skater/tree/master/examples/third_party_model

Interpretation Examples

Global Interpretation

1. Model Agnostic Partial Dependence Plot(PDP)

   • https://github.com/datascienceinc/Skater/blob/master/examples/ensemble_model.ipynb
   • https://github.com/datascienceinc/Skater/blob/master/examples/sklearn-classifiers.ipynb
   • https://github.com/datascienceinc/Skater/blob/master/examples/sklearn_regression_models.ipynb

2. Model Agnostic Feature Importance

   • https://github.com/datascienceinc/Skater/blob/master/examples/ensemble_model.ipynb
   • https://github.com/datascienceinc/Skater/blob/master/examples/sklearn-classifiers.ipynb
   • https://github.com/datascienceinc/Skater/blob/master/examples/sklearn_regression_models.ipynb

Local Interpretation

1. Local Interpretable Model Explanations(LIME)
   • https://github.com/datascienceinc/Skater/blob/master/examples/image_interpretation_example.ipynb
   • https://github.com/datascienceinc/Skater/blob/master/examples/NLP.ipynb
   • https://github.com/datascienceinc/Skater/blob/master/examples/third_party_model/algorithmia_indico.ipynb

2. DeepInterpreter for interpreting DNNs

• epsilon-Layer-wise Relevance Propagation(e-LRP): only for image currently
• Integrated Gradient(IG): image and text
• Occlusion: only for image currently

Image Interpretability

• Image Classification:

  • https://github.com/datascienceinc/Skater/blob/master/examples/image_interpretability/image_interpretation_example_cats_dogs.ipynb
  • https://github.com/datascienceinc/Skater/blob/master/examples/image_interpretability/imagenet_adv_inceptionv3_tensorflow.ipynb
  • https://github.com/datascienceinc/Skater/blob/master/examples/image_interpretability/mnist_cnn_keras.ipynb
  • https://github.com/datascienceinc/Skater/blob/master/examples/image_interpretability/mnist_mlp_tensorflow.ipynb

  • Toy Example on self driving car:

    https://github.com/datascienceinc/Skater/blob/master/examples/image_interpretability/self_driving_toy_example/toy_self_driving_example.ipynb

Text Interpretability with Integrated Gradient

• Sentiment Analysis:

  • https://github.com/datascienceinc/Skater/blob/master/examples/text_interpretability/LSTM_sentiment_imdb.ipynb
  • https://github.com/datascienceinc/Skater/blob/master/examples/text_interpretability/cnn_sentiment_imdb.ipynb

Global And Local Interpretation

1. Rule Based Models(Transparent Design)
   • https://github.com/datascienceinc/Skater/blob/master/examples/rule_list_notebooks/rule_lists_continuous_features.ipynb
   • https://github.com/datascienceinc/Skater/blob/master/examples/rule_list_notebooks/rule_lists_titanic_dataset.ipynb