model

Type Members

class AnomalyDetectionAttributes extends ModelAttributes with HasAnomalyDetectionAttributes

Holds attributes of an Anomaly Detection Model.
class AnomalyDetectionModel extends Model with HasWrappedAnomalyDetectionAttributes

Anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a data set.
class AnomalyDetectionOutput extends RegOutputs
class AssociationAttributes extends ModelAttributes with HasAssociationAttributes
class AssociationModel extends Model with HasWrappedAssociationAttributes

The Association Rule model represents rules where some set of items is associated to another set of items.
class AssociationOutputs extends ModelOutputs with HasAssociationRules
class AssociationRule extends HasPredictedValue with HasEntityId with HasConfidence with PmmlElement

We consider association rules of the form "<antecedent itemset> => <consequent itemset>" next:
class Attribute extends Predicate with PmmlElement

Defines input attributes for each scorecard characteristic are defined in terms of predicates.
class BaseCumHazardTables extends PmmlElement
class BaselineCell extends PmmlElement
class BaselineStratum extends PmmlElement
class BayesInput extends PmmlElement

For a discrete field, each BayesInput contains the counts pairing the discrete values of that field with those of the target field.
class BayesInputs extends PmmlElement

Contains several BayesInput elements.
class BayesOutput extends PmmlElement

Contains the counts associated with the values of the target field.
class Categories extends PmmlElement
class Category extends PmmlElement
class Characteristic extends PmmlElement

Defines the point allocation strategy for each scorecard characteristic (numeric or categorical).
class Characteristics extends PmmlElement

Envelopes for all scorecard characteristics.
class Cluster extends PmmlElement

A cluster is defined by its center vector or by statistics.
class ClusteringAttributes extends ModelAttributes with HasClusteringAttributes
class ClusteringField extends PmmlElement
class ClusteringModel extends Model with HasWrappedClusteringAttributes

A cluster model basically consists of a set of clusters.
class ClusteringOutputs extends CluOutputs
class Coefficient extends PmmlElement

Coefficient αi is described
class Coefficients extends PmmlElement

Used to store the support vector coefficients αi and b.
class Comparisons extends PmmlElement

Comparisons is a matrix which contains the similarity values or distance values, depending on the attribute modelClass in ClusteringModel.
class ComplexPartialScore extends RegressionEvaluator with PmmlElement

Defines ComplexPartialScore, the actual partial score is the value returned by the EXPRESSION (see org.pmml4s .transformations for more information).
class CompoundRule extends Rule with PmmlElement

CompoundRule consists of a predicate and one or more rules.
class Con extends PmmlElement

Defines the connections coming into that parent element.
class Covariances extends PmmlElement

Stores coordinate-by-coordinate variances (diagonal cells) and covariances (non-diagonal cells).
class CovariateList extends PmmlElement

List of covariate names.
class DataModel extends Model

DataModel is a container for all info about metadata, it's the parent model of all predictive models.
class DecisionTree extends EmbeddedModel
abstract class EmbeddedModel extends Model

Model Composition
class EventValues extends PmmlElement
class FactorList extends PmmlElement

List of factor (categorical predictor) names.
class GeneralRegressionAttributes extends ModelAttributes with HasGeneralRegressionAttributes
class GeneralRegressionModel extends Model with HasWrappedGeneralRegressionAttributes

Definition of a general regression model.
class GeneralRegressionOutputs extends MixedClsWithRegOutputs
trait HasAnomalyDetectionAttributes extends HasModelAttributes
trait HasAssociationAttributes extends HasModelAttributes
trait HasClusteringAttributes extends HasModelAttributes
trait HasGeneralRegressionAttributes extends HasModelAttributes
trait HasNaiveBayesAttributes extends HasModelAttributes
trait HasNearestNeighborAttributes extends HasModelAttributes
trait HasNeuralNetworkAttributes extends HasModelAttributes
trait HasRegressionAttributes extends HasModelAttributes
trait HasScorecardAttributes extends HasModelAttributes
trait HasSupportVectorMachineAttributes extends HasModelAttributes
trait HasTreeAttributes extends HasModelAttributes
trait HasWrappedAnomalyDetectionAttributes extends HasWrappedModelAttributes with HasAnomalyDetectionAttributes
trait HasWrappedAssociationAttributes extends HasWrappedModelAttributes with HasAssociationAttributes
trait HasWrappedClusteringAttributes extends HasWrappedModelAttributes with HasClusteringAttributes
trait HasWrappedGeneralRegressionAttributes extends HasWrappedModelAttributes with HasGeneralRegressionAttributes
trait HasWrappedNaiveBayesAttributes extends HasWrappedModelAttributes with HasNaiveBayesAttributes
trait HasWrappedNearestNeighborAttributes extends HasWrappedModelAttributes with HasNearestNeighborAttributes
trait HasWrappedNeuralNetworkAttributes extends HasWrappedModelAttributes with HasNeuralNetworkAttributes
trait HasWrappedRegressionAttributes extends HasWrappedModelAttributes with HasRegressionAttributes
trait HasWrappedScorecardAttributes extends HasWrappedModelAttributes with HasScorecardAttributes
trait HasWrappedSupportVectorMachineAttributes extends HasWrappedModelAttributes with HasSupportVectorMachineAttributes
trait HasWrappedTreeAttributes extends HasWrappedModelAttributes with HasTreeAttributes
class InstanceField extends PmmlElement
class InstanceFields extends PmmlElement

Serves as an envelope for all the fields included in the training instances.
class Item extends PmmlElement

Obviously the id of an Item must be unique.
class ItemRef extends PmmlElement

Item references point to elements of type Item
class Itemset extends PmmlElement
class KNNInput extends PmmlElement
class KNNInputs extends PmmlElement

encapsulates several KNNInput elements which define the fields used to query the k-NN model, one KNNInput element per field.
trait KernelType extends AnyRef
class KohonenMap extends PmmlElement

The element KohonenMap is appropriate for clustering models that were produced by a Kohonen map algorithm.
class LinearKernelType extends KernelType with PmmlElement

Linear basis functions which lead to a hyperplane as classifier.
class MeanClusterDistances extends PmmlElement

Contains an array of non-negative real values, it is required when the algorithm type is clusterMeanDist.
class MiningModel extends Model with HasWrappedModelAttributes

The element MiningModel allows precise specification of the usage of multiple models within one PMML file.
class MiningOutputs extends ClsOutputs with RegOutputs with CluOutputs with SegmentOutputs
class MissingValueWeights extends PmmlElement

MissingValueWeights is used to adjust distance or similarity measures for missing data.
abstract class Model extends HasParent with HasVersion with HasWrappedModelAttributes with HasMiningSchema with HasOutput with HasModelStats with HasModelExplanation with HasTargets with HasLocalTransformations with FieldScope with ModelLocation with HasTargetFields with Predictable with HasModelVerification with PmmlElement

Abstract class that represents a PMML model
sealed trait ModelElement extends AnyRef
trait ModelLocation extends AnyRef
class MutableModel extends Model
class NaiveBayesAttributes extends ModelAttributes with HasNaiveBayesAttributes
class NaiveBayesModel extends Model with HasWrappedNaiveBayesAttributes

Naïve Bayes uses Bayes' Theorem, combined with a ("naive") presumption of conditional independence, to predict the value of a target (output), from evidence given by one or more predictor (input) fields.
class NaiveBayesOutputs extends ClsOutputs
class NearestNeighborAttributes extends ModelAttributes with HasNearestNeighborAttributes
class NearestNeighborModel extends Model with HasWrappedNearestNeighborAttributes

k-Nearest Neighbors (k-NN) is an instance-based learning algorithm.
class NearestNeighborModelOutputs extends KNNOutputs
class NeuralInput extends PmmlElement

Defines how input fields are normalized so that the values can be processed in the neural network.
class NeuralInputs extends PmmlElement

An input neuron represents the normalized value for an input field.
class NeuralLayer extends PmmlElement
class NeuralNetwork extends Model with HasWrappedNeuralNetworkAttributes

A neural network has one or more input nodes and one or more neurons.
class NeuralNetworkAttributes extends ModelAttributes with HasNeuralNetworkAttributes
class NeuralNetworkOutputs extends MixedClsWithRegOutputs
class NeuralOutput extends PmmlElement

Defines how the output of the neural network must be interpreted.
class NeuralOutputs extends PmmlElement
class Neuron extends PmmlElement

Contains an identifier id which must be unique in all layers.
class Node extends Predicate with HasScoreDistributions

This element is an encapsulation for either defining a split or a leaf in a tree model.
class PCell extends PmmlElement

Cell in the ParamMatrix.
class PCovCell extends PmmlElement
class PCovMatrix extends PmmlElement

Matrix of Parameter estimate covariances.
class PPCell extends PmmlElement

Cell in the PPMatrix.
class PPMatrix extends PmmlElement

Predictor-to-Parameter correlation matrix.
class PairCounts extends PmmlElement

PairCounts lists, for a field Ii's discrete value Iij, the TargetValueCounts that pair the value Iij with each value of the target field.
class ParamMatrix extends PmmlElement

Parameter matrix.
class Parameter extends PmmlElement

Each Parameter contains a required name and optional label.
class ParameterList extends PmmlElement

Lists all Parameters.
class PolynomialKernelType extends KernelType with PmmlElement

Polynomial basis functions which lead to a polynome classifier.
class Predictor extends PmmlElement

Describes a categorical (factor) or a continuous (covariate) predictor for the model.
class RadialBasisKernelType extends KernelType with PmmlElement

Radial basis functions, the most common kernel type K(x,y) = exp(-gamma*||x - y||2)
class Regression extends EmbeddedModel
class RegressionAttributes extends ModelAttributes with HasRegressionAttributes
class RegressionModel extends Model with HasWrappedRegressionAttributes

The regression functions are used to determine the relationship between the dependent variable (target field) and one or more independent variables.
class RegressionOutputs extends MixedClsWithRegOutputs
sealed trait Rule extends AnyRef
class RuleSelectionMethod extends PmmlElement

Describes how rules are selected to apply the model to a new case
class RuleSet extends PmmlElement
class RuleSetModel extends Model with HasWrappedModelAttributes

Ruleset models can be thought of as flattened decision tree models.
class RuleSetOutputs extends ModelOutputs with MutablePredictedValue with MutableConfidence
class SVMOutputs extends MixedClsWithRegOutputs
class Scorecard extends Model with HasWrappedScorecardAttributes

A data mining model contains a set of input fields which are used to predict a certain target value.
class ScorecardAttributes extends ModelAttributes with HasScorecardAttributes

Holds attributes of a Scorecard.
class ScorecardOutput extends RegOutputs with MutableReasonCodes
class Segment extends Predictable with Predicate with PmmlElement
class Segmentation extends PmmlElement
class SigmoidKernelType extends KernelType with PmmlElement

Sigmoid kernel functions for some models of Neural Network type K(x,y) = tanh(gamma*<x,y>+coef0)
class SimpleRule extends Rule with HasScoreDistributions with PmmlElement

SimpleRule consists of an identifier, a predicate, a score and information on rule performance.
class SupportVector extends PmmlElement

SupportVector which only has the attribute vectorId - the reference to the support vector in VectorDictionary.
class SupportVectorMachine extends PmmlElement

Holds a single instance of an SVM.
class SupportVectorMachineAttributes extends ModelAttributes with HasSupportVectorMachineAttributes
class SupportVectorMachineModel extends Model with HasWrappedSupportVectorMachineAttributes

Support Vector Machine models for classification and regression are considered.
class SupportVectors extends PmmlElement

Contains all support vectors required for the respective SVM instance.
class TargetValueCount extends PmmlElement
class TargetValueCounts extends PmmlElement

Lists the counts associated with each value of the target field, However, a TargetValueCount whose count is zero may be omitted.
class TargetValueStat extends PmmlElement

Used for a continuous input field Ii to define statistical measures associated with each value of the target field.
class TargetValueStats extends PmmlElement

Serves as the envelope for element TargetValueStat.
class TrainingInstances extends PmmlElement

Encapsulates the definition of the fields included in the training instances as well as their values.
class TransformationModel extends DataModel
class TreeAttributes extends ModelAttributes with HasTreeAttributes

Holds attributes of a Tree model
class TreeModel extends Model with HasWrappedTreeAttributes

The TreeModel in PMML allows for defining either a classification or prediction structure.
class TreeOutputs extends MixedClsWithRegOutputs with MutableConfidence with MutableEntityId
class VariableWeight extends PmmlElement
class VectorDictionary extends PmmlElement

Contains the set of support vectors which are of the typeVectorInstance.
class VectorFields extends PmmlElement

Defines which entries in the vectors correspond to which fields.
class VectorInstance extends PmmlElement

A data vector given in dense or sparse array format.

Value Members

object ActivationFunction extends Enumeration
object AlgorithmType extends Enumeration

Defines model types used by the anomaly model.
object BaselineMethod extends Enumeration

An informational string describing the technique used by the model designer to establish the baseline scores.
object CatScoringMethod extends Enumeration
object ContScoringMethod extends Enumeration
object Criterion extends Enumeration
object CumulativeLinkFunction extends Enumeration

Definition is used for specifying a cumulative link function used in ordinalMultinomial model.
object Distribution extends Enumeration

The probability distribution of the dependent variable for generalizedLinear model.
object GeneralModelType extends Enumeration

Specifies the type of regression model in use.
object KernelType
object LinkFunction extends Enumeration

Definition is used for specifies the type of link function to use when generalizedLinear model type is specified.
object MissingPredictionTreatment extends Enumeration

The missing prediction treatment options are used when at least one model for which the predicate in the Segment evaluates to true has a missing result.
object MissingValueStrategy extends Enumeration

Defines a strategy for dealing with missing values.
object Model extends Serializable
object ModelClass extends Enumeration
object ModelElement
object MultipleModelMethod extends Enumeration

Specifying how all the models applicable to a record should be combined.
object NNNormalizationMethod extends Enumeration

A normalization method softmax ( pj = exp(yj) / Sumi(exp(yi) ) ) or simplemax ( pj = yj / Sumi(yi) ) can be applied to the computed activation values.
object NoTrueChildStrategy extends Enumeration

Defines what to do in situations where scoring cannot reach a leaf node.
object PCovMatrixType extends Enumeration
object ReasonCodeAlgorithm extends Enumeration

Describes how reason codes shall be ranked.
object RegressionModelType extends Enumeration

Specifies the type of a regression model.
object RegressionNormalizationMethod extends Enumeration

Describes how the prediction is converted into a confidence value (aka probability).
object Rule
object SVMClassificationMethod extends Enumeration

The two most popular methods for multi-class classification are one-against-all (also known as one-against-rest) and one-against-one.
object SVMRepresentation extends Enumeration

Usually the SVM model uses support vectors to define the model function.
object SplitCharacteristic extends Enumeration

Indicates whether non-leaf Nodes in the tree model have exactly two children, or an unrestricted number of children.

package model

Type Members

class AnomalyDetectionAttributes extends ModelAttributes with HasAnomalyDetectionAttributes

class AnomalyDetectionModel extends Model with HasWrappedAnomalyDetectionAttributes

class AnomalyDetectionOutput extends RegOutputs

class AssociationAttributes extends ModelAttributes with HasAssociationAttributes

class AssociationModel extends Model with HasWrappedAssociationAttributes

class AssociationOutputs extends ModelOutputs with HasAssociationRules

class AssociationRule extends HasPredictedValue with HasEntityId with HasConfidence with PmmlElement

class Attribute extends Predicate with PmmlElement

class BaseCumHazardTables extends PmmlElement

class BaselineCell extends PmmlElement

class BaselineStratum extends PmmlElement

class BayesInput extends PmmlElement

class BayesInputs extends PmmlElement

class BayesOutput extends PmmlElement

class Categories extends PmmlElement

class Category extends PmmlElement

class Characteristic extends PmmlElement

class Characteristics extends PmmlElement

class Cluster extends PmmlElement

class ClusteringAttributes extends ModelAttributes with HasClusteringAttributes

class ClusteringField extends PmmlElement

class ClusteringModel extends Model with HasWrappedClusteringAttributes

class ClusteringOutputs extends CluOutputs

class Coefficient extends PmmlElement

class Coefficients extends PmmlElement

class Comparisons extends PmmlElement

class ComplexPartialScore extends RegressionEvaluator with PmmlElement

class CompoundRule extends Rule with PmmlElement

class Con extends PmmlElement

class Covariances extends PmmlElement

class CovariateList extends PmmlElement

class DataModel extends Model

class DecisionTree extends EmbeddedModel

abstract class EmbeddedModel extends Model

class EventValues extends PmmlElement

class FactorList extends PmmlElement

class GeneralRegressionAttributes extends ModelAttributes with HasGeneralRegressionAttributes

class GeneralRegressionModel extends Model with HasWrappedGeneralRegressionAttributes

class GeneralRegressionOutputs extends MixedClsWithRegOutputs

trait HasAnomalyDetectionAttributes extends HasModelAttributes

trait HasAssociationAttributes extends HasModelAttributes

trait HasClusteringAttributes extends HasModelAttributes

trait HasGeneralRegressionAttributes extends HasModelAttributes

trait HasNaiveBayesAttributes extends HasModelAttributes

trait HasNearestNeighborAttributes extends HasModelAttributes

trait HasNeuralNetworkAttributes extends HasModelAttributes

trait HasRegressionAttributes extends HasModelAttributes

trait HasScorecardAttributes extends HasModelAttributes

trait HasSupportVectorMachineAttributes extends HasModelAttributes

trait HasTreeAttributes extends HasModelAttributes

trait HasWrappedAnomalyDetectionAttributes extends HasWrappedModelAttributes with HasAnomalyDetectionAttributes

trait HasWrappedAssociationAttributes extends HasWrappedModelAttributes with HasAssociationAttributes

trait HasWrappedClusteringAttributes extends HasWrappedModelAttributes with HasClusteringAttributes

trait HasWrappedGeneralRegressionAttributes extends HasWrappedModelAttributes with HasGeneralRegressionAttributes

trait HasWrappedNaiveBayesAttributes extends HasWrappedModelAttributes with HasNaiveBayesAttributes

trait HasWrappedNearestNeighborAttributes extends HasWrappedModelAttributes with HasNearestNeighborAttributes

trait HasWrappedNeuralNetworkAttributes extends HasWrappedModelAttributes with HasNeuralNetworkAttributes

trait HasWrappedRegressionAttributes extends HasWrappedModelAttributes with HasRegressionAttributes

trait HasWrappedScorecardAttributes extends HasWrappedModelAttributes with HasScorecardAttributes

trait HasWrappedSupportVectorMachineAttributes extends HasWrappedModelAttributes with HasSupportVectorMachineAttributes

trait HasWrappedTreeAttributes extends HasWrappedModelAttributes with HasTreeAttributes

class InstanceField extends PmmlElement

class InstanceFields extends PmmlElement

class Item extends PmmlElement

class ItemRef extends PmmlElement

class Itemset extends PmmlElement

class KNNInput extends PmmlElement

class KNNInputs extends PmmlElement

trait KernelType extends AnyRef

class KohonenMap extends PmmlElement

class LinearKernelType extends KernelType with PmmlElement

class MeanClusterDistances extends PmmlElement

class MiningModel extends Model with HasWrappedModelAttributes

class MiningOutputs extends ClsOutputs with RegOutputs with CluOutputs with SegmentOutputs

class MissingValueWeights extends PmmlElement

sealed trait ModelElement extends AnyRef

trait ModelLocation extends AnyRef