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csinva / imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
https://csinva.io/imodels
MIT License
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SkopeRules output #16

Closed ukamath closed 3 years ago

ukamath commented 3 years ago

Hello Thanks for consolidating the implementations into one nice package. I was running SkopeRules on the diabetes dataset and saw that the results are ('Insulin > 142.0 and Age > 26.5', (0.8732394366197183, 0.7005649717514124, 1)) ('Insulin <= 187.5 and Insulin > 121.0 and Age > 24.5', (0.8862208393458393, 0.6502540183068366, 3)) ('Insulin <= 169.75 and Insulin > 168.75', (1.0, 0.5337078651685393, 1)) ('Insulin > 121.0 and BMI > 30.300000190734863 and Age <= 27.5', (0.5128579777907656, 0.17596669877528553, 2)) ('Glucose <= 167.5 and Insulin > 169.75', (0.38333333333333336, 0.12921348314606743, 1)) ('Insulin <= 169.75 and Insulin > 143.0 and Age <= 26.5', (0.6923076923076923, 0.10465116279069768, 1))

Looking at the code, I see that the first two elements after the Rule are precision and recall, what is the third integer? Thanks Uday

csinva commented 3 years ago

Sorry we'll hide that info going forward...it is basically the number of points in the rule overlapping with other existing rules (used for doing deduplication, but not very informative afterwards).