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A selection of interpretable methods with logging and printouts

Project description

This is a library with 3 interepretable machine learning methods, wrapped with logging and side by side comparison. They can be used as normal scikit learn models, with fit, predict, and find_accuracy methods. Or, a script can be run on a data set, which will run all three and return logs and accuracies.

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Files for InterpretableMLWrappers, version 0.0.2.1
Filename, size & hash File type Python version Upload date
InterpretableMLWrappers-0.0.2.1-py3-none-any.whl (14.1 kB) View hashes Wheel py3
InterpretableMLWrappers-0.0.2.1.tar.gz (21.6 kB) View hashes Source None

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