target: field that was used a training target for supervised models.
predicted: field whose value is predicted by the model. As of PMML 4.2, this is deprecated and it has been
replaced by the usage type target.
supplementary: field holding additional descriptive information. Supplementary fields are not required to apply a
model. They are provided as additional information for explanatory purpose, though. When some field has gone through
preprocessing transformations before a model is built, then an additional supplementary field is typically used to
describe the statistics for the original field values.
group: field similar to the SQL GROUP BY. For example, this is used by AssociationModel and SequenceModel to group
items into transactions by customerID or by transactionID.
order: This field defines the order of items or transactions and is currently used in SequenceModel and
TimeSeriesModel. Similarly to group, it is motivated by the SQL syntax, namely by the ORDER BY statement.
frequencyWeight and analysisWeight: These fields are not needed for scoring, but provide very important information
on how the model was built. Frequency weight usually has positive integer values and is sometimes called "replication
weight". Its values can be interpreted as the number of times each record appears in the data. Analysis weight can
have fractional positive values, it could be used for regression weight in regression models or for case weight in
trees, etc. It can be interpreted as different importance of the cases in the model. Counts in ModelStats and
Partitions can be computed using frequency weight, mean and standard deviation values can be computed using both
weights.
Linear Supertypes
Enumeration, Serializable, Serializable, AnyRef, Any
Usage type