model-validation-toolkit
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Model Validation Toolkit is a collection of tools to assist with validating machine learning models prior to deploying them to production and monitoring them after deployment to production.
Model Validation Tookit
Installation
Run pip install mvtk.
Windows users: Until Jaxlib is supported on windows natively you will need to either use this library from a Linux subsystem or within a Docker container. Alternatively, you can build jaxlib from source.
Developers
Check out this repository and cd into the directory.
Run pip install -e ".[doc]".
The [doc] is used to install dependencies for building documentation. You
will need pandoc installed.
Submodules
You can import:
mvtk.credibilityfor assessing credibility from sample size.mvtk.interprenetfor building interpretable neural nets.mvtk.thresholdingfor adaptive thresholding.mvtk.sobolfor Sobol sensitivity analysismvtk.supervisorfor divergence analysismvtk.metricsfor specialised metricsmvtk.bias_variancefor bias-variance decomposition
Documentation
You can run make -C docs html on a Mac or make.bat -C docs html on a PC to just rebuild the docs. In this case, point your browser to docs/_build/html/index.html to view the homepage. If your browser was already pointing to documentation that you changed, you can refresh the page to see the changes.