Prerequisites

To ensure proper DataComp functionality some basic assumptions have to be met by the datasets:

• Tabular data formats need to be used (.csv, .tsv, excel etc.)
• Data points / entities are represented as rows
• Features / variables should be columns
• Feature names should be equivalent among the datasets - semantically equal features should bear the same name. Features that are named differently will be treated as features that are not in common.
• Feature values should be represented in the same way (e.g. same variable coding, same categories for discrete variables)
• Any data alternations (e.g. normalization) should be carried out the same way on the features to be compared. Otherwise they will influence comparison results

Common Errors

Make sure that numeric feature columns hold solely numeric data and/or missing values (nan’s). String values like for example “>90” must be converted into numerical values other wise errors will occur.