root

root/org.pmml4s.common/HasModelAttributes

HasModelAttributes

trait HasModelAttributes

Holds common attributes of a PMML model.

class Object

trait Matchable

class Any

trait HasWrappedModelAttributes

trait HasWrappedAnomalyDetectionAttributes

class AnomalyDetectionModel

trait HasWrappedAssociationAttributes

class AssociationModel

trait HasWrappedClusteringAttributes

class ClusteringModel

trait HasWrappedGeneralRegressionAttributes

class GeneralRegressionModel

trait HasWrappedNaiveBayesAttributes

class NaiveBayesModel

trait HasWrappedNearestNeighborAttributes

class NearestNeighborModel

trait HasWrappedNeuralNetworkAttributes

class NeuralNetwork

trait HasWrappedRegressionAttributes

class RegressionModel

trait HasWrappedScorecardAttributes

class Scorecard

trait HasWrappedSupportVectorMachineAttributes

class SupportVectorMachineModel

trait HasWrappedTreeAttributes

class TreeModel

class MiningModel

class Model

class DataModel

class TransformationModel

class EmbeddedModel

class DecisionTree

class Regression

class MutableModel

class MutableAnomalyDetectionModel

class MutableMiningModel

class RuleSetModel

class ModelAttributes

class AnomalyDetectionAttributes

class AssociationAttributes

class ClusteringAttributes

class GeneralRegressionAttributes

class NaiveBayesAttributes

class NearestNeighborAttributes

class NeuralNetworkAttributes

class RegressionAttributes

class ScorecardAttributes

class SupportVectorMachineAttributes

class TreeAttributes

trait HasAnomalyDetectionAttributes

trait HasAssociationAttributes

trait HasClusteringAttributes

trait HasGeneralRegressionAttributes

trait HasNaiveBayesAttributes

trait HasNearestNeighborAttributes

trait HasNeuralNetworkAttributes

trait HasRegressionAttributes

trait HasScorecardAttributes

trait HasSupportVectorMachineAttributes

trait HasTreeAttributes

Value members

Abstract methods

The algorithm name is free-type and can be any description for the specific algorithm that produced the model. This attribute is for information only.

The algorithm name is free-type and can be any description for the specific algorithm that produced the model. This attribute is for information only.

Describe the kind of mining model, e.g., whether it is intended to be used for clustering or for classification.

Describe the kind of mining model, e.g., whether it is intended to be used for clustering or for classification.

Indicates if the model is valid for scoring. If this attribute is true or if it is missing, then the model should be processed normally. However, if the attribute is false, then the model producer has indicated that this model is intended for information purposes only and should not be used to generate results.

Indicates if the model is valid for scoring. If this attribute is true or if it is missing, then the model should be processed normally. However, if the attribute is false, then the model producer has indicated that this model is intended for information purposes only and should not be used to generate results.

Identifies the model with a unique name in the context of the PMML file. This attribute is not required. Consumers of PMML models are free to manage the names of the models at their discretion.

Identifies the model with a unique name in the context of the PMML file. This attribute is not required. Consumers of PMML models are free to manage the names of the models at their discretion.

Concrete methods

Tests if this is a association rules model.

Tests if this is a association rules model.

Tests if this is a classification model.

Tests if this is a classification model.

Tests if this is a clustering model.

Tests if this is a clustering model.

Tests if this is a mixed model.

Tests if this is a mixed model.

Tests if this is a regression model.

Tests if this is a regression model.

Tests if this is a sequences model.

Tests if this is a sequences model.

Tests if this is a time series model.

Tests if this is a time series model.