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timmens / causal-forest

Implements the Causal Forest algorithm formulated in Athey and Wager (2018).
MIT License
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Check for compatibility with sklearn functionals. #12

Open timmens opened 4 years ago

timmens commented 4 years ago

Change API to sklearn standard --even though treatment effect estimation is a mix between supervised and unsupervised learning and therefore any estimator can never utilize the features of sklearn it eases readability and consistency.

To do:

  1. Construct estimator class cforest which implements a fit and predict method.
  2. Hide all other functionalities
  3. Check if there is any compatibility with sklearn.
timmens commented 4 years ago

In commit (d95a7cfa0cc019b10bd0738fbd186f4e73c81613) I implemented a wrapper class CausalForest which implements the methods fit, predict, save and load.

What remains to be done:

  1. Check if I can hide private functions
  2. Check for compatibility with sklearn