Abstract class for field in a PMML with common implementations.
Contains definitions for fields as used in mining models.
Contains definitions for fields as used in mining models. It specifies the types and value ranges. These definitions are assumed to be independent of specific data sets as used for training or scoring a specific model.
Defines a field as used in mining models.
Defines a field as used in mining models. It specifies the types and value ranges.
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, ...) as well as policies for treating missing, invalid or outlier values.
The MiningSchema is the Gate Keeper for its model element.
The MiningSchema is the Gate Keeper for its model element. All data entering a model must pass through the MiningSchema. Each model element contains one MiningSchema which lists fields as used in that model. While the MiningSchema contains information that is specific to a certain model, the DataDictionary contains data definitions which do not vary per model. The main purpose of the MiningSchema is to list the fields that have to be provided in order to apply the model.
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.
OutputField elements specify names, types and rules for calculating specific result features. This information can be used while writing an output table.
Note that castInteger, min, max, rescaleConstant and rescaleFactor only apply to models of type regression.
Note that castInteger, min, max, rescaleConstant and rescaleFactor only apply to models of type regression. Furthermore, they must be applied in sequence, which is:
min and max rescaleFactor rescaleConstant castInteger
Defines the wrapped field that contains an internal field acts all operations.
Specifies which scoring algorithm to use when computing the output value.
Specifies which scoring algorithm to use when computing the output value. It applies only to Association Rules models.
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.
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.
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. Except as described above, the missingValueTreatment attribute just indicates how the missingValueReplacement was derived, but places no behavioral requirement on the consumer.
Outliers
Outliers
Applies only to Association Rules and is used to specify which criterion is used to sort the output result.
Applies only to Association Rules and is used to specify which criterion is used to sort the output result. For instance, the result could be sorted by the confidence, support or lift of the rules.
Determines the sorting order when ranking the results.
Determines the sorting order when ranking the results. The default behavior (rankOrder="descending") indicates that the result with the highest rank will appear first on the sorted list.
Result Features
Specifies which feature of an association rule to return.
Specifies which feature of an association rule to return. This attribute has been deprecated as of PMML 4.2. The rule feature values can now be specified in the feature attribute.
Usage type
Usage type