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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
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InterpretableMLWrappers- (14.1 kB) View hashes Wheel py3
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