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tmadl / sklearn-expertsys

Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
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Pip installable? #10

Open springcoil opened 8 years ago

springcoil commented 8 years ago

Hi is it possible to wrap this up into a pip or even better conda installable?

csinva commented 5 years ago

Hello, for anyone still interested, I made a python3 port of this code which is now pip-installable:

pip install git+https://github.com/csinva/interpretability-implementations-demos

from imodels import RuleListClassifier
model = RuleListClassifier()
model.fit(X_train, y_train)
model.score(X_test, y_test)
preds = model.predict(X_test)
pratyushaj commented 5 years ago

pip install git+https://github.com/csinva/interpretability-implementations-demos

For anyone using this, instead of from imodels import RuleListClassifier, use from imodels.bayesian_rule_lists import RuleListClassifier.

Thanks for making this pip-able!

Sandy4321 commented 4 years ago

so is it still only python 2 after python 2 is discontinued?