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jphall663 / interpretable_machine_learning_with_python

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Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

python data-science machine-learning data-mining h2o gradient-boosting-machine transparency decision-tree fairness lime accountability interpretability interpretable-ai interpretable-ml xai fatml interpretable interpretable-machine-learning iml machine-learning-interpretability
  • Updated Feb 10, 2021
  • Jupyter Notebook

oegedijk / explainerdashboard

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Addition: SimplifiedRegressionDashbaord

oegedijk
oegedijk commented Nov 17, 2020

The default dashboard can be very overwhelming with lots of tabs, toggles and dropdowns. It would be nice to offer a simplified version. This can be built as a custom ExplainerComponent and included in custom, so that you could e.g.:

from explainerdashboard import RegressionExplainer, ExplainerDashboard
from explainerdashboard.custom import SimplifiedRegressionDashboard

explainer = Reg
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good first issue
pyss3

sergioburdisso / pyss3

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A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:

nlp machine-learning natural-language-processing text-mining data-mining text-classification machine-learning-algorithms artificial-intelligence document-classification sentence-classification interpretability multilabel-classification explainable-artificial-intelligence interpretable-ml xai interpretable-machine-learning document-categorization early-classification text-labeling ss3-classifier
  • Updated Feb 10, 2021
  • Python

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