Validity check for features across samples

raamana / pyradigm

Research data management in biomedical and machine learning applications

http://raamana.github.io/pyradigm/

MIT License

28 stars 12 forks source link

Closed raamana closed 5 years ago

raamana commented 5 years ago

After various samples are added, and user is ready to save MLDataset, it may be helpful to apply some sanity checks such as

presence of NaNs or Inf
a feature being constant across all subjects, which is either useless, or worse indicative of a serious bug on the user side
two or more subjects having identical features

And give the user an option to make it an error or warning!!