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
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- By Inheritance
- Model
- PmmlElement
- Serializable
- HasExtensions
- HasModelVerification
- Predictable
- HasTargetFields
- ModelLocation
- FieldScope
- HasField
- HasLocalTransformations
- HasTargets
- HasModelExplanation
- HasModelStats
- HasOutput
- HasMiningSchema
- HasWrappedModelAttributes
- HasModelAttributes
- HasVersion
- HasParent
- AnyRef
- Any
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- Public
- Protected
Instance Constructors
- new Model()
Abstract Value Members
- abstract def attributes: ModelAttributes
Common attributes of this model
Common attributes of this model
- Definition Classes
- HasWrappedModelAttributes
- abstract def createOutputs(): ModelOutputs
Creates an object of subclass of ModelOutputs that is for writing into an output series.
- abstract def localTransformations: Option[LocalTransformations]
The optional local transformations.
The optional local transformations.
- Definition Classes
- HasLocalTransformations
- abstract def miningSchema: MiningSchema
- Definition Classes
- HasMiningSchema
- abstract def modelElement: ModelElement
Model element type.
- abstract def modelExplanation: Option[ModelExplanation]
- Definition Classes
- HasModelExplanation
- abstract def modelStats: Option[ModelStats]
- Definition Classes
- HasModelStats
- abstract def modelVerification: Option[ModelVerification]
- Definition Classes
- HasModelVerification
- abstract def output: Option[Output]
- Definition Classes
- HasOutput
- abstract val parent: Model
The parent model.
The parent model.
- Definition Classes
- HasParent
- abstract def predict(values: Series): Series
Predicts values for a given data series.
Predicts values for a given data series.
- Definition Classes
- Model → Predictable
- abstract def targets: Option[Targets]
- Definition Classes
- HasTargets
Concrete Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def algorithmName: Option[String]
The algorithm name is free-type and can be any description for the specific algorithm that produced the model.
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.
- Definition Classes
- HasWrappedModelAttributes → HasModelAttributes
- def anyMissing(series: Series): Boolean
Returns true if there are any missing values of all input fields in the specified series.
Returns true if there are any missing values of all input fields in the specified series.
- Attributes
- protected
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def candidateOutputFields: Array[OutputField]
- Definition Classes
- HasOutput
- def candidateOutputSchema: StructType
The schema of candidate outputs.
- def classes(name: String): Array[Any]
Returns class labels of the specified target.
- lazy val classes: Array[Any]
The class labels in a classification model.
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- def combineOutputFields(listA: Array[OutputField], listB: Array[OutputField]): Array[OutputField]
- Definition Classes
- HasOutput
- def containInterResults: Boolean
- Definition Classes
- HasOutput
- val customOutputFields: Array[OutputField]
User-defined custom output fields, both the internal output of PMML and predefined output are ignored when the field is specified.
User-defined custom output fields, both the internal output of PMML and predefined output are ignored when the field is specified.
- Definition Classes
- HasOutput
- def dVersion: Double
Returns PMML version as a double value
Returns PMML version as a double value
- Definition Classes
- HasVersion
- def dataDictionary: DataDictionary
The data dictionary of this model.
- def defaultOutputFields: Array[OutputField]
Returns all candidates output fields of this model when there is no output specified explicitly.
- def encode(series: Series): DSeries
Encodes the input series.
Encodes the input series.
- Attributes
- protected
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def extensions: Seq[Extension]
- Definition Classes
- HasExtensions
- def field(name: String): Field
Returns the field of a given name.
Returns the field of a given name.
- Definition Classes
- HasField
- Exceptions thrown
FieldNotFoundExceptionif a field with the given name does not exist
- def fieldsOfUsageType(typ: UsageType): Array[Field]
Get fields by its usage type: 'active', 'target', 'predicted', 'group' and so on
- def functionName: MiningFunction
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.
- Definition Classes
- HasWrappedModelAttributes → HasModelAttributes
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- def getField(name: String): Option[Field]
Returns the field of a given name, None if a field with the given name does not exist.
- def hasExtensions: Boolean
- Definition Classes
- HasExtensions
- def hasTarget: Boolean
- Definition Classes
- HasTargetFields
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- def header: Header
The header of this model.
- lazy val implicitInputDerivedFields: Array[Field]
Implicit referenced derived fields for the sub-model except ones defined in the mining schema.
- def importances: Map[String, Double]
Returns importances of predictors.
- def inferClasses: Array[Any]
The sub-classes can override this method to provide classes of target inside model.
- lazy val inputDerivedFields: Array[Field]
Referenced derived fields.
- lazy val inputFields: Array[Field]
All input fields in an array.
- lazy val inputNames: Array[String]
All input names in an array.
- lazy val inputSchema: StructType
The schema of inputs.
- def isAssociationRules: Boolean
Tests if this is a association rules model.
Tests if this is a association rules model.
- Definition Classes
- HasModelAttributes
- def isBinary: Boolean
Tests if the target is a binary field
- def isClassification(name: String): Boolean
Tests if this is a classification model of the specified target, it's applicable for multiple targets.
- def isClassification: Boolean
Tests if this is a classification model.
Tests if this is a classification model.
- Definition Classes
- Model → HasModelAttributes
- def isClustering: Boolean
Tests if this is a clustering model.
Tests if this is a clustering model.
- Definition Classes
- HasModelAttributes
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def isMixed: Boolean
Tests if this is a mixed model.
Tests if this is a mixed model.
- Definition Classes
- HasModelAttributes
- def isOrdinal: Boolean
Tests if the target is an ordinal field
- def isPredictionOnly: Boolean
- Definition Classes
- HasOutput
- def isRegression(name: String): Boolean
Tests if this is a regression model of the specified target, it's applicable for multiple targets.
- def isRegression: Boolean
Tests if this is a regression model.
Tests if this is a regression model.
- Definition Classes
- Model → HasModelAttributes
- def isScorable: Boolean
Indicates if the model is valid for scoring.
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.
- Definition Classes
- HasWrappedModelAttributes → HasModelAttributes
- def isSequences: Boolean
Tests if this is a sequences model.
Tests if this is a sequences model.
- Definition Classes
- HasModelAttributes
- val isSubModel: Boolean
- Definition Classes
- ModelLocation
- def isTimeSeries: Boolean
Tests if this is a time series model.
Tests if this is a time series model.
- Definition Classes
- HasModelAttributes
- val isTopLevelModel: Boolean
- Definition Classes
- ModelLocation
- def modelName: Option[String]
Identifies the model with a unique name in the context of the PMML file.
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.
- Definition Classes
- HasWrappedModelAttributes → HasModelAttributes
- def multiTargets: Boolean
- Definition Classes
- HasTargetFields
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @IntrinsicCandidate() @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @IntrinsicCandidate() @native()
- lazy val nullSeries: Series
A series with all null values is returned when can not produce a result.
- def numClasses(name: String): Int
Returns the number of class labels of the specified target.
- lazy val numClasses: Int
The number of class labels in a classification model.
- def opType(name: String): OpType
Returns optype of the specified target.
- lazy val opType: OpType
When Target specifies optype then it overrides the optype attribute in a corresponding MiningField, if it exists.
When Target specifies optype then it overrides the optype attribute in a corresponding MiningField, if it exists. If the target does not specify optype then the MiningField is used as default. And, in turn, if the MiningField does not specify an optype, it is taken from the corresponding DataField. In other words, a MiningField overrides a DataField, and a Target overrides a MiningField.
- def outputFields: Array[OutputField]
- Definition Classes
- HasOutput
- def outputIndex(feature: ResultFeature, value: Option[Any] = None): Int
- Definition Classes
- HasOutput
- def outputNames: Array[String]
- Definition Classes
- HasOutput
- def outputSchema: StructType
The schema of final outputs.
- def postClassification(name: String = null): (Any, Map[Any, Double])
- Attributes
- protected
- def postPredictedValue(outputs: MutablePredictedValue, name: String = null): MutablePredictedValue
- Attributes
- protected
- def postRegression(predictedValue: Any, name: String = null): Any
- Attributes
- protected
- def predict(it: Iterator[Series]): Iterator[Series]
- def predict(json: String): String
Predicts one or multiple records in json format, there are two formats supported:
Predicts one or multiple records in json format, there are two formats supported:
- ‘records’ : list like [{column -> value}, … , {column -> value}] - ‘split’ : dict like {‘columns’ -> [columns], ‘data’ -> [values]}
- json
Records in json
- returns
Results in json
- def predict(values: List[Any]): List[Any]
- def predict[T](values: Array[T]): Array[Any]
Predicts values for a given Array, and the order of those values is supposed as same as the input fields list
- def predict(values: (String, Any)*): Seq[(String, Any)]
Predicts values for a given list of key/value pairs.
- def predict(values: Map[String, Any]): Map[String, Any]
Predicts values for a given data map of Java.
- def predict(values: Map[String, Any]): Map[String, Any]
Predicts values for a given data map.
- lazy val predictedValueIndex: Int
- Definition Classes
- HasOutput
- def prepare(series: Series): (Series, Boolean)
Pre-process the input series.
Pre-process the input series.
- Attributes
- protected
- def probabilitiesSupported: Boolean
Tests if probabilities of categories of target can be produced by this model.
- def result(series: Series, modelOutputs: ModelOutputs, fields: Array[OutputField] = Array.empty): Series
- Attributes
- protected
- def setOutputFields(outputFields: Array[OutputField]): Model.this.type
- Definition Classes
- HasOutput
- def setParent(parent: Model): Model.this.type
- Definition Classes
- HasParent
- def setSupplementOutput(value: Boolean): Model.this.type
- Definition Classes
- HasOutput
- def singleTarget: Boolean
- Definition Classes
- HasTargetFields
- def size: Int
- Definition Classes
- HasTargetFields
- val supplementOutput: Boolean
A flag for whether to return those predefined output fields not exist in the output element explicitly.
A flag for whether to return those predefined output fields not exist in the output element explicitly.
- Definition Classes
- HasOutput
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- lazy val targetClasses: Map[String, Array[Any]]
The class labels of all categorical targets.
- lazy val targetField: Field
The first target field for the supervised model.
- lazy val targetFields: Array[Field]
All target fields in an array.
All target fields in an array. Multiple target fields are allowed. It depends on the kind of the model whether prediction of multiple fields is supported.
- def targetFieldsOfResidual: Array[Field]
Returns targets that are residual values to be computed, the input data must include target values.
Returns targets that are residual values to be computed, the input data must include target values.
- Definition Classes
- HasOutput
- def targetName: String
Name of the first target for the supervised model.
Name of the first target for the supervised model.
- Definition Classes
- HasTargetFields
- lazy val targetNames: Array[String]
All target names in an array.
All target names in an array.
- Definition Classes
- Model → HasTargetFields
- def targetNamesOfResidual: Array[String]
- Definition Classes
- HasOutput
- def toString(): String
- Definition Classes
- AnyRef → Any
- def transformationDictionary: Option[TransformationDictionary]
The optional transformation dictionary.
- def unionCandidateOutputFields: Array[OutputField]
- Definition Classes
- HasOutput
- def unionOutputFields: Array[OutputField]
- Definition Classes
- HasOutput
- lazy val usedFields: Array[Field]
Setup indices to retrieve data from series faster by index instead of name, the index is immutable when model is built because the model object could run in multiple threads, so it's important make sure the model object is totally immutable.
Setup indices to retrieve data from series faster by index instead of name, the index is immutable when model is built because the model object could run in multiple threads, so it's important make sure the model object is totally immutable.
Setup indices of targets that are usually not used by the scoring process, they are only used when residual values to be computed.
- lazy val usedSchema: StructType
The schema of used fields.
- def version: String
PMML version.
PMML version.
- Definition Classes
- HasVersion
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)