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Commits on Jul 26, 2019

• minor improvements to figures

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Commits on Jul 25, 2019

• some testing/comments

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Commits on Jul 23, 2019

• add shap vs. resid stuff

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• rerun logloss shap

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Commits on Jul 22, 2019

• add residual plots and disparate error analysis

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• more steps on residual analysis

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Commits on May 23, 2019

• proofing entire debugging notebook

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Commits on May 22, 2019

• more analysis of results

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Commits on May 21, 2019

• more extensibility for adversary generating/summarizing functions

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• more sensitivity analysis

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Commits on May 16, 2019

• some text for model debugging with sensitivity analysis

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Commits on May 15, 2019

• add random attack

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Commits on May 14, 2019

• more on adversaries

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Commits on May 13, 2019

• first steps toward adversaries

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Commits on Apr 15, 2019

• first steps toward adversarial examples

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Commits on Apr 9, 2019

• first draft of new PDP/ICE for model debugging

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Commits on Apr 8, 2019

• more incremental progress on model debugging: PDP

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• Merge branch 'ph_add_errors' of https://github.com/jphall663/interpretable_machine_learning_with_python into ph_add_errors

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• reset dia.ipynb back to master

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Commits on Apr 3, 2019

• fix a few broken hyperlinks

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• add aquarium instructions

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• add aquarium instructions

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• Merge branch 'master' of https://github.com/jphall663/interpretable_machine_learning_with_python into ph_add_errors

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Commits on Mar 22, 2019

• freeze h2o for reproducibility, slight update to resid analysis results

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Commits on Mar 15, 2019

• freeze xgboost for reproducibility

  

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Commits on Mar 5, 2019

• new takes on model debugging

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• add disclaimer

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• update to master

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• add disclaimer

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• add disclaimer

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• Merge branch 'master' of https://github.com/jphall663/interpretable_machine_learning_with_python

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• add disclaimer

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• add disclaimer

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Commits on Feb 3, 2019

• some intermediate commit necessary for merge

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Commits on Jan 24, 2019

• more formatting

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