> Could it be possible to make missing_values_transform=None by default and then assume missing_values_transform is the same as missing_values_fit? I think it is the most common use, isn't it?

Ok

> Is there a use case for encoding missing value differently at fit and transform time? Also is there a use case for encoding missing values with more than one value?

I two cases:
* with a Pipeline
* for matrix completion (I'll probably use 0 for the missing values and np.nan for the missing values that should be imputed)