Type Members

1.  case class AboveInterval(leftMargin: Double, isOpen: Boolean) extends Interval with Product with Serializable
2.  class AnyDistribution extends ContinuousDistribution
3.  class Application extends PmmlElement

   Describes the software application that generated the model.

4.  case class BelowInterval(rightMargin: Double, isOpen: Boolean) extends Interval with Product with Serializable
5.  class BooleanType extends DataType

   The data type representing Boolean values.

6.  class CategoricalPredictor extends RegressionPredictor

   Defines a categorical independent variable.

   Defines a categorical independent variable. The list of attributes comprises the name of the variable, the value attribute, and the coefficient by which the values of this variable must be multiplied.

7.  trait Clearable extends AnyRef
8.  trait ClsOutputs extends ModelOutputs with MutablePredictedValueWithProbabilities with MutablePredictedDisplayValue
9.  trait CluOutputs extends ModelOutputs with MutablePredictedValue with MutablePredictedDisplayValue with MutableEntityId with MutableAffinities
10.  class ComparisonMeasure extends PmmlElement
11.  class CompoundPredicate extends Predicate

    CompoundPredicate: an encapsulating element for combining two or more elements as defined at the entity PREDICATE.

    CompoundPredicate: an encapsulating element for combining two or more elements as defined at the entity PREDICATE. The attribute associated with this element, booleanOperator, can take one of the following logical (boolean) operators: and, or, xor or surrogate.

12.  trait ContinuousDistribution extends PmmlElement
13.  class ContrastMatrixFactorPredictor extends FactorPredictor
14.  class Counts extends PmmlElement

    Carries counters for frequency of values with respect to their state of being missing, invalid, or valid.

    Carries counters for frequency of values with respect to their state of being missing, invalid, or valid. The counts can be non-integer if they are weighted.

15.  class CovariatePredictor extends RegressionPredictor
16.  sealed abstract class DataType extends DataTypeLike

    The base type of all PMML data types.

17.  trait DataTypeLike extends Serializable

    A template trait for a data type.

18.  case class DateDaySinceYearType(aYear: Int) extends DateType with Product with Serializable

    The type dateDaysSince[aYear] is a variant of the type date where the values are represented as the number of days since aYear-01-01.

    The type dateDaysSince[aYear] is a variant of the type date where the values are represented as the number of days since aYear-01-01. The date aYear-01-01 is represented by the number 0. aYear-01-02 is represented by 1, aYear-02-01 is represented by 31, etc. Dates before aYear-01-01 are represented as negative numbers. For example, values of type dateDaysSince[1960] are the number of days since 1960-01-01. The date 1960-01-01 is represented by the number 0.

19.  case class DateTimeSecondSinceYearType(aYear: Int) extends DateTimeType with Product with Serializable

    The type dateTimeSecondsSince[aYear] is a variant of the type date where the values are represented as the number of seconds since 00:00 on aYear-01-01.

    The type dateTimeSecondsSince[aYear] is a variant of the type date where the values are represented as the number of seconds since 00:00 on aYear-01-01. The datetime 00:00:00 on aYear-01-01 is represented by the number 0. The datetime 00:00:01 on aYear-01-01 is represented by 1, etc. Datetimes before aYear-01-01 are represented as negative numbers. For example, values of type dateTimeSecondsSince[1960] are the number of seconds since 00:00 on 1960-01-01. The datetime 00:00:00 on 1960-01-01 is represented by the number 0. The datetime 00:01:00 on 1960-01-01 is represented by 60.

20.  sealed abstract class DateTimeType extends NumericType

    The base type of timestamp

21.  sealed abstract class DateType extends NumericType

    The base type of date

22.  class DenseMatrix extends Matrix

    Dense matrix

23.  class DenseVector[V] extends Vector[V]
24.  class DiagonalMatrix extends Matrix

    The content is just one array of numbers representing the diagonal values.

25.  trait Distance extends PmmlElement
26.  trait DoubleEvaluator extends PmmlElement
27.  trait Evaluator extends PmmlElement

    A common super-trait that accepts a series, then evaluates a single value.

28.  case class Extension(extender: Option[String], name: Option[String], value: Option[Any], content: Option[Any]) extends Serializable with Product
29.  class FactorPredictor extends CategoricalPredictor
30.  class GaussianDistribution extends ContinuousDistribution
31.  case class GenericInterval(leftMargin: Double, rightMargin: Double, closure: Closure) extends Interval with Product with Serializable
32.  class GenericMultiModelOutputs extends MultiModelOutputs
33.  trait HasAffinities extends AnyRef
34.  trait HasAssociationRules extends AnyRef
35.  trait HasConfidence extends AnyRef
36.  trait HasDataType extends DataTypeLike
37.  trait HasDecision extends AnyRef
38.  trait HasEntityId extends AnyRef
39.  trait HasEntityIds extends AnyRef
40.  trait HasExtensions extends AnyRef

    The PMML schema contains a mechanism for extending the content of a model.

    The PMML schema contains a mechanism for extending the content of a model. Extension elements should be present as the first child in all elements and groups defined in PMML. This way it is possible to place information in the Extension elements which affects how the remaining entries are treated. The main element in each model should have Extension elements as the first and the last child for maximum flexibility.

41.  trait HasIntervals extends AnyRef
42.  trait HasModelAttributes extends AnyRef

    Holds common attributes of a PMML model.

43.  trait HasModelExplanation extends AnyRef
44.  trait HasModelStats extends AnyRef
45.  trait HasModelVerification extends AnyRef
46.  trait HasOpType extends AnyRef
47.  trait HasParent extends AnyRef
48.  trait HasPredictedDisplayValue extends AnyRef
49.  trait HasPredictedValue extends AnyRef
50.  trait HasPredictedValueWithProbabilities extends HasPredictedValue with HasProbabilities
51.  trait HasProbabilities extends AnyRef
52.  trait HasReasonCode extends AnyRef
53.  trait HasReasonCodes extends AnyRef
54.  trait HasResidual extends AnyRef
55.  trait HasScoreDistributions extends AnyRef
56.  trait HasSegment extends HasTransformedValue
57.  trait HasStandardError extends AnyRef
58.  trait HasTransformedValue extends AnyRef
59.  trait HasVersion extends AnyRef
60.  trait HasWarning extends AnyRef
61.  trait HasWrappedModelAttributes extends HasModelAttributes
62.  class Header extends PmmlElement

63.  class InlineTable extends Table
64.  class IntegerType extends NumericType

    The data type representing Int or Long values.

65.  sealed abstract class Interval extends PmmlElement

    Defines a range of numeric values.

66.  trait KNNOutputs extends ModelOutputs with MutablePredictedValue with MutablePredictedDisplayValue with MutableEntityIds with MutableAffinities
67.  case class MatCell(row: Int, col: Int, value: Double) extends Product with Serializable
68.  trait Matrix extends PmmlElement

    Trait for a matrix.

69.  trait MixedClsWithRegOutputs extends ClsOutputs with RegOutputs
70.  trait MixedEvaluator extends Evaluator with DoubleEvaluator
71.  class ModelAttributes extends HasModelAttributes with Serializable

    Class represents common attributes of a PMML model.

72.  class ModelExplanation extends PmmlElement

    Model Explanation

73.  trait ModelOutputs extends AnyRef
74.  class ModelStats extends PmmlElement

    Provides a basic framework for representing variable statistics.

75.  class ModelVerification extends PmmlElement

    Provides a dataset of model inputs and known results that can be used to verify accurate results are generated, regardless of the environment.

76.  trait MultiModelOutputs extends ModelOutputs
77.  trait MutableAffinities extends HasAffinities
78.  trait MutableConfidence extends HasConfidence
79.  trait MutableEntityId extends HasEntityId
80.  trait MutableEntityIds extends HasEntityIds
81.  trait MutablePredictedDisplayValue extends HasPredictedDisplayValue
82.  trait MutablePredictedValue extends HasPredictedValue
83.  trait MutablePredictedValueWithProbabilities extends HasPredictedValueWithProbabilities with MutablePredictedValue with MutableProbabilities
84.  trait MutableProbabilities extends HasProbabilities
85.  trait MutableReasonCodes extends HasReasonCodes
86.  trait MutableSegment extends HasSegment
87.  class NumericInfo extends PmmlElement

    The values for mean, minimum, maximum and standardDeviation are defined as usual.

    The values for mean, minimum, maximum and standardDeviation are defined as usual. median is calculated as the 50% quantile; interQuartileRange is calculated as (75% quantile - 25% quantile).

88.  class NumericPredictor extends RegressionPredictor

    Defines a numeric independent variable.

    Defines a numeric independent variable. The list of valid attributes comprises the name of the variable, the exponent to be used, and the coefficient by which the values of this variable must be multiplied. Note that the exponent defaults to 1, hence it is not always necessary to specify. Also, if the input value is missing, the result evaluates to a missing value.

89.  sealed abstract class NumericType extends DataType

    Numeric data types.

90.  sealed trait OpType extends AnyRef

    Indicates which operations are defined on the values.

91.  class Partition extends PmmlElement

    A Partition contains statistics for a subset of records, for example it can describe the population in a cluster.

    A Partition contains statistics for a subset of records, for example it can describe the population in a cluster. The content of a Partition mirrors the definition of the general univariate statistics. That is, each Partition describes the distribution per field. For each field there can be information about frequencies, numeric moments, etc.

    The attribute name identifies the Partition. The attribute size is the number of records. All aggregates in PartitionFieldStats must have size = totalFrequency in Counts if specified.

92.  class PartitionFieldStats extends PmmlElement

    field references to (the name of) a MiningField for background statistics.

    field references to (the name of) a MiningField for background statistics. The sequence of NUM-ARRAYs is the same as for ContStats. For categorical fields there is only one array containing the frequencies; for numeric fields, the second and third array contain the sums of values and the sums of squared values, respectively. The number of values in each array must match the number of categories or intervals in UnivariateStats of the field.

93.  trait PmmlElement extends HasExtensions with Serializable

    The base trait for all elements of PMML

94.  case class PointInterval(x: Double) extends Interval with Product with Serializable
95.  class PoissonDistribution extends ContinuousDistribution
96.  trait Predicate extends PmmlElement
97.  trait Predictable extends AnyRef
98.  class PredictorTerm extends RegressionPredictor

    Contains one or more fields that are combined by multiplication.

    Contains one or more fields that are combined by multiplication. That is, this element supports interaction terms. The type of all fields referenced within PredictorTerm must be continuous. Note that if the input value is missing, the result evaluates to a missing value.

99.  class Quantile extends PmmlElement

100.  class RealType extends NumericType

     The data type representing Float or Double values.

101.  trait RegOutputs extends ModelOutputs with MutablePredictedValue
102.  trait RegressionEvaluator extends Evaluator with DoubleEvaluator
103.  class RegressionParameter extends RegressionPredictor
104.  sealed trait RegressionPredictor extends RegressionEvaluator
105.  class RegressionTable extends RegressionPredictor

     Lists the values of all predictors or independent variables.

     Lists the values of all predictors or independent variables. If the model is used to predict a numerical field, then there is only one RegressionTable and the attribute targetCategory may be missing. If the model is used to predict a categorical field, then there are two or more RegressionTables and each one must have the attribute targetCategory defined with a unique value.

106.  class Row extends AnyRef
107.  class ScoreDistribution extends PmmlElement

     Comprises a method to list predicted values in a classification trees structure.

108.  class ScoreDistributions extends PmmlElement
109.  trait SegmentOutputs extends ModelOutputs with MutableSegment
110.  class SimplePredicate extends Predicate

     Defines a rule in the form of a simple boolean expression.

     Defines a rule in the form of a simple boolean expression. The rule consists of field, operator (booleanOperator) for binary comparison, and value.

111.  class SimpleSetPredicate extends Predicate

     Checks whether a field value is element of a set.

     Checks whether a field value is element of a set. The set of values is specified by the array.

112.  class SparseMatrix extends Matrix

     Column-major sparse matrix.

113.  class SparseVector[V] extends Vector[V]
114.  class StringType extends DataType

     The data type representing String values.

115.  case class StructField(name: String, dataType: DataType) extends Product with Serializable

     A field inside a StructType.

     A field inside a StructType.

     name

     The name of this field.

     dataType

     The data type of this field.

116.  case class StructType(fields: Array[StructField]) extends DataType with Seq[StructField] with Product with Serializable

     StructType defines a type for a [Series]

117.  class SymmetricMatrix extends Matrix

     The content must be represented by Arrays.

     The content must be represented by Arrays. The first array contains the matrix element M(0,0), the second array contains M(1,0), M(1,1), and so on (that is the lower left triangle). Other elements are defined by symmetry.

118.  sealed trait Table extends PmmlElement
119.  class TableLocator extends Table
120.  class TimeSecondsType extends TimeType

     The type timeSeconds is a variant of the type time where the values are represented as the number of seconds since 00:00, that is, since midnight.

     The type timeSeconds is a variant of the type time where the values are represented as the number of seconds since 00:00, that is, since midnight. The time 00:00 is represented by the number 0. No negative values are allowed.

121.  class TimeType extends NumericType

     The data type representing Time values.

122.  trait Transformer extends AnyRef

     Abstract class for transformers that transform one series into another.

123.  class UniformDistribution extends ContinuousDistribution
124.  class Value extends PmmlElement
125.  trait Vector[V] extends AnyRef
126.  class binarySimilarity extends Distance
127.  class minkowski extends Distance