Sometimes, data might be in a tidy form but have missing attributes.
Common attributes for dealing with missing attributes are:
- Removing the examples with missing attributes from the dataset (if your dataset is big enough to safely sacrifice some data).
- Using a learning algorithm that can deal with missing attribute values (e.g. the decision tree learning algorithm)
- Using a Data Imputation technique.
Data Sampling