Add experimental missing data support for GCM #1304
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The current implementation has the following limits: - Only missing data in numerical features are supported - Auto assignment only considers non-linear models for missing data - Auto assignment only considers 3 different model types - Not all GCM methods are supported. For example, distribution change based on missing data does not work due to the independence tests. - Not tested thoroughly To use the data with missing values, experimental_allow_nans has to be set to True in the assign_causal_mechanisms method. Manual model assignment should work as well. Signed-off-by: Patrick Bloebaum <[email protected]>
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The current implementation has the following limits:
To use the data with missing values, experimental_allow_nans has to be set to True in the assign_causal_mechanisms method. Manual model assignment should work as well.
Addresses: #1300