Apply defines the application of a function.
Constant values can be used in expressions which have multiple arguments.
Defines new (user-defined) functions as variations or compositions of existing functions or transformations.
Provides a common element for the various mappings.
Discretization of numerical input fields is a mapping from continuous to discrete values using intervals.
Trait of Expression that defines how the values of the new field are computed.
Field references are simply pass-throughs to fields previously defined in the DataDictionary, a DerivedField, or a result field.
LocalTransformations holds derived fields that are local to the model.
Any discrete value can be mapped to any possibly different discrete value by listing the pairs of values.
Normalization provides a basic framework for mapping input values to specific value ranges, usually the numeric range [0 .
Encode string values into numeric values in order to perform mathematical computations.
The TextIndex element fully configures how the text in textField should be processed and translated into a frequency metric for a particular term of interest.
A TextIndexNormalization element offers more advanced ways of normalizing text input into a more controlled vocabulary that corresponds to the terms being used in invocations of this indexing function.
The TransformationDictionary allows for transformations to be defined once and used by any model element in the PMML document.
- allHits: count all hits - bestHits: count all hits with the lowest Levenshtein distance
- termFrequency: use the number of times the term occurs in the document (x = freqi).
Defines several user-defined functions produced by various vendors, actually, well-defined "DefineFunction" is fully supported by pmml4s, while some could be not.
At various places the mining models use simple functions in order to map user data to values that are easier to use in the specific model. For example, neural networks internally work with numbers, usually in the range from 0 to 1. Numeric input data are mapped to the range [0..1], and categorical fields are mapped to series of 0/1 indicators.
PMML defines various kinds of simple data transformations: