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Doubly robust models renaming + multiple treatment-feature options #28

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merged 6 commits into from
Jan 25, 2022

Commits on Jan 25, 2022

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  5. Multiple treatment-based features in PropensityFeatureStandardization

    Adds several options for propensity features:
     1. inverse-propensity weight: 1/Pr[A=a_i|X].
     2. inverse-propensity matrix: 1/Pr[A=a|X] for all possible `a`s.
     3. propensity vector: Pr[A=1|X]
     4. logit-transformed propensities: logit(Pr[A=1|X])
     5. propensity matrix: Pr[A=a|X] for all possible `a`s.
    
    Also adds corresponding tests for these options.
    ehudkr committed Jan 25, 2022
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