Comments (5)
SuStaIn doesn't handle missing data at the moment, I have an idea about one way to go about it but it needs testing first
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Yeah, I had a think about how to do it without biassing the model, but it's not as straightforward as it is for the EBM.
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I close this as we have ongoing work on missing variable analysis in SuStaIn at the POND group, to be introduced later.
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Any updates on handling missing data?
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@d-morrison — see ZScoreSustainMissingData if using the z score model. If using mixture SustaIn, then you have to handle missing data yourself when calculating the event likelihoods that go into pySuStaIn.
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Related Issues (20)
- Fixing controls in GMM HOT 2
- `use_parallel_startpoints` fails on numpy 1.21 HOT 6
- Fix for "rare" divide by zero problem HOT 6
- Idea: SusStaIn constraint with longitudinal measures HOT 6
- Adding a colourbar to PVD plots HOT 6
- IndexError while running the SuStaIn Workshop file HOT 2
- Data Preparation Pipeline/Code HOT 5
- How to interpret the Positional Variance Diagram HOT 1
- Question on Using pySuStaIn on ADNI HOT 3
- Parallel CV doesn't work (aka "Why do all my CV jobs run for fold 0 only???") HOT 1
- Ordinal Sustain Notebook HOT 3
- Mislabelled subtype numbers in PVDs HOT 9
- Parallelization fails -- TypeError: cannot pickle '_abc._abc_data' object HOT 4
- Allow for complete model reloading HOT 2
- minor installation issue with sklearn HOT 1
- [Question] Can we discover subtypes in a training test, and use the discovered subtypes to subtype subjects of a test set? HOT 1
- Example code for mixture_KDE HOT 3
- ValueError in AbstractSuStaIn HOT 10
- Enabling PVD Plot Legends HOT 1
- Apply the trained model to external/independent data HOT 2
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