Abstract class for field in a PMML with common implementations.
Contains definitions for fields as used in mining models.
Defines a field as used in mining models.
The Decisions element contains an element Decision for every possible value of the decision.
Abstract class for field in a PMML.
The Output section in the model specifies names for columns in an output table and describes how to compute the corresponding values.
MiningFields also define the usage of each field (active, supplementary, target, .
The MiningSchema is the Gate Keeper for its model element.
Output element describes a set of result values that can be returned from a model.
OutputField elements specify names, types and rules for calculating specific result features.
Note that castInteger, min, max, rescaleConstant and rescaleFactor only apply to models of type regression.
Defines the wrapped field that contains an internal field acts all operations.
Specifies which scoring algorithm to use when computing the output value.
If a regression model should predict integers, use the attribute castInteger to control how decimal places should be handled.
This field specifies how invalid input values are handled.
In a PMML consumer this field is for information only, unless the value is returnInvalid, in which case if a missing value is encountered in the given field, the model should return a value indicating an invalid result; otherwise, the consumer only looks at missingValueReplacement - if a value is present it replaces missing values.
Outliers
Applies only to Association Rules and is used to specify which criterion is used to sort the output result.
Determines the sorting order when ranking the results.
Result Features
Specifies which feature of an association rule to return.
Usage type