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1.1.1b4
  • Overview
  • Install Skater
  • Tutorial
  • API Reference
  • Gallery
    • Model Abstraction
      • InMemory Model
      • Deployed Model
    • Interpretation Examples
      • Global Interpretation
      • Local Interpretation
      • Global And Local Interpretation
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Gallery¶

Model Abstraction¶

_images/ml_workflow.png

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¶

_images/pdp.png
  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
_images/feature_importance.png
  1. 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¶

_images/lime.png
  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

  1. 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
Interpreting pre-trained Inception-V3 model some more examples on image interpretability input image for steering left inference on steering prediction using e-LRP, Integrated Gradient and Occlusion
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
_images/text_ig.png
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¶

_images/sbrl.png
  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
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