Packages

c

org.pmml4s.model

AssociationModel

class AssociationModel extends Model with HasWrappedAssociationAttributes

The Association Rule model represents rules where some set of items is associated to another set of items. For example a rule can express that a certain product or set of products is often bought in combination with a certain set of other products, also known as Market Basket Analysis. An Association Rule model typically has two variables: one for grouping records together into transactions (usageType="group") and another that uniquely identifies each record (usageType="active"). Alternatively, association rule models can be built on regular data, where each category of each categorical field is an item. Yet another possible format of data is a table with true/false values, where only the fields having true value in a record are considered valid items.

An Association Rule model consists of four major parts: - Model attributes - Items - ItemSets - AssociationRules

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Inherited
  1. AssociationModel
  2. HasWrappedAssociationAttributes
  3. HasAssociationAttributes
  4. Model
  5. PmmlElement
  6. Serializable
  7. HasExtensions
  8. HasModelVerification
  9. Predictable
  10. HasTargetFields
  11. ModelLocation
  12. FieldScope
  13. HasField
  14. HasLocalTransformations
  15. HasTargets
  16. HasModelExplanation
  17. HasModelStats
  18. HasOutput
  19. HasMiningSchema
  20. HasWrappedModelAttributes
  21. HasModelAttributes
  22. HasVersion
  23. HasParent
  24. AnyRef
  25. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new AssociationModel(parent: Model, attributes: AssociationAttributes, miningSchema: MiningSchema, items: Array[Item], itemsets: Array[Itemset], associationRules: Array[AssociationRule], output: Option[Output] = None, targets: Option[Targets] = None, localTransformations: Option[LocalTransformations] = None, modelStats: Option[ModelStats] = None, modelExplanation: Option[ModelExplanation] = None, modelVerification: Option[ModelVerification] = None, extensions: Seq[Extension] = immutable.Seq.empty)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. val activeField: Field
  5. val activeFields: Array[Field]
  6. val activeNames: Array[String]
  7. 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
    HasWrappedModelAttributesHasModelAttributes
  8. 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
    Definition Classes
    Model
  9. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  10. val associationRules: Array[AssociationRule]
  11. val attributes: AssociationAttributes

    Common attributes of this model

    Common attributes of this model

    Definition Classes
    AssociationModelHasWrappedAssociationAttributesHasWrappedModelAttributes
  12. def avgNumberOfItemsPerTA: Option[Double]

    The average number of items contained in a transaction.

    The average number of items contained in a transaction.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  13. def candidateOutputFields: Array[OutputField]
    Definition Classes
    HasOutput
  14. def candidateOutputSchema: StructType

    The schema of candidate outputs.

    The schema of candidate outputs.

    Definition Classes
    Model
  15. def classes(name: String): Array[Any]

    Returns class labels of the specified target.

    Returns class labels of the specified target.

    Definition Classes
    Model
  16. lazy val classes: Array[Any]

    The class labels in a classification model.

    The class labels in a classification model.

    Definition Classes
    Model
  17. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native()
  18. def combineOutputFields(listA: Array[OutputField], listB: Array[OutputField]): Array[OutputField]
    Definition Classes
    HasOutput
  19. def containInterResults: Boolean
    Definition Classes
    HasOutput
  20. def createOutputs(): AssociationOutputs

    Creates an object of subclass of ModelOutputs that is for writing into an output series.

    Creates an object of subclass of ModelOutputs that is for writing into an output series.

    Definition Classes
    AssociationModelModel
  21. 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
  22. def dVersion: Double

    Returns PMML version as a double value

    Returns PMML version as a double value

    Definition Classes
    HasVersion
  23. def dataDictionary: DataDictionary

    The data dictionary of this model.

    The data dictionary of this model.

    Definition Classes
    Model
  24. def defaultOutputFields: Array[OutputField]

    Returns all candidates output fields of this model when there is no output specified explicitly.

    Returns all candidates output fields of this model when there is no output specified explicitly.

    Definition Classes
    ModelHasOutput
  25. def encode(series: Series): DSeries

    Encodes the input series.

    Encodes the input series.

    Attributes
    protected
    Definition Classes
    Model
  26. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  27. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  28. val extensions: Seq[Extension]
    Definition Classes
    AssociationModelHasExtensions
  29. def field(name: String): Field

    Returns the field of a given name.

    Returns the field of a given name.

    Definition Classes
    HasField
    Exceptions thrown

    FieldNotFoundException if a field with the given name does not exist

  30. def fieldsOfUsageType(typ: UsageType): Array[Field]

    Get fields by its usage type: 'active', 'target', 'predicted', 'group' and so on

    Get fields by its usage type: 'active', 'target', 'predicted', 'group' and so on

    Definition Classes
    Model
  31. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable])
  32. 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
    HasWrappedModelAttributesHasModelAttributes
  33. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  34. def getField(name: String): Option[Field]

    Returns the field of a given name, None if a field with the given name does not exist.

    Returns the field of a given name, None if a field with the given name does not exist.

    Definition Classes
    ModelHasField
  35. val groupField: Field
  36. def hasExtensions: Boolean
    Definition Classes
    HasExtensions
  37. def hasTarget: Boolean
    Definition Classes
    HasTargetFields
  38. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  39. def header: Header

    The header of this model.

    The header of this model.

    Definition Classes
    Model
  40. lazy val implicitInputDerivedFields: Array[Field]

    Implicit referenced derived fields for the sub-model except ones defined in the mining schema.

    Implicit referenced derived fields for the sub-model except ones defined in the mining schema.

    Definition Classes
    Model
  41. def importances: Map[String, Double]

    Returns importances of predictors.

    Returns importances of predictors.

    Definition Classes
    Model
  42. def inferClasses: Array[Any]

    The sub-classes can override this method to provide classes of target inside model.

    The sub-classes can override this method to provide classes of target inside model.

    Definition Classes
    Model
  43. lazy val inputDerivedFields: Array[Field]

    Referenced derived fields.

    Referenced derived fields.

    Definition Classes
    Model
  44. lazy val inputFields: Array[Field]

    All input fields in an array.

    All input fields in an array.

    Definition Classes
    Model
  45. lazy val inputNames: Array[String]

    All input names in an array.

    All input names in an array.

    Definition Classes
    Model
  46. lazy val inputSchema: StructType

    The schema of inputs.

    The schema of inputs.

    Definition Classes
    Model
  47. def isAssociationRules: Boolean

    Tests if this is a association rules model.

    Tests if this is a association rules model.

    Definition Classes
    HasModelAttributes
  48. def isBinary: Boolean

    Tests if the target is a binary field

    Tests if the target is a binary field

    Definition Classes
    Model
  49. def isClassification(name: String): Boolean

    Tests if this is a classification model of the specified target, it's applicable for multiple targets.

    Tests if this is a classification model of the specified target, it's applicable for multiple targets.

    Definition Classes
    Model
  50. def isClassification: Boolean

    Tests if this is a classification model.

    Tests if this is a classification model.

    Definition Classes
    ModelHasModelAttributes
  51. def isClustering: Boolean

    Tests if this is a clustering model.

    Tests if this is a clustering model.

    Definition Classes
    HasModelAttributes
  52. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  53. def isMixed: Boolean

    Tests if this is a mixed model.

    Tests if this is a mixed model.

    Definition Classes
    HasModelAttributes
  54. def isOrdinal: Boolean

    Tests if the target is an ordinal field

    Tests if the target is an ordinal field

    Definition Classes
    Model
  55. def isPredictionOnly: Boolean
    Definition Classes
    HasOutput
  56. def isRegression(name: String): Boolean

    Tests if this is a regression model of the specified target, it's applicable for multiple targets.

    Tests if this is a regression model of the specified target, it's applicable for multiple targets.

    Definition Classes
    Model
  57. def isRegression: Boolean

    Tests if this is a regression model.

    Tests if this is a regression model.

    Definition Classes
    ModelHasModelAttributes
  58. 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
    HasWrappedModelAttributesHasModelAttributes
  59. def isSequences: Boolean

    Tests if this is a sequences model.

    Tests if this is a sequences model.

    Definition Classes
    HasModelAttributes
  60. def isSubModel: Boolean
    Definition Classes
    ModelLocation
  61. def isTimeSeries: Boolean

    Tests if this is a time series model.

    Tests if this is a time series model.

    Definition Classes
    HasModelAttributes
  62. def isTopLevelModel: Boolean
    Definition Classes
    ModelLocation
  63. val items: Array[Item]
  64. val itemsets: Array[Itemset]
  65. def lengthLimit: Option[Int]

    The maximum number of items contained in a rule which was used to limit the number of rules.

    The maximum number of items contained in a rule which was used to limit the number of rules.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  66. val localTransformations: Option[LocalTransformations]

    The optional local transformations.

    The optional local transformations.

    Definition Classes
    AssociationModelHasLocalTransformations
  67. def maxNumberOfItemsPerTA: Option[Int]

    The number of items contained in the largest transaction.

    The number of items contained in the largest transaction.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  68. def minimumConfidence: Double

    The minimum confidence value satisfied by all rules.

    The minimum confidence value satisfied by all rules. Confidence is calculated as (support (rule) / support(antecedent)).

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  69. def minimumSupport: Double

    The minimum relative support value (#supporting transactions / #total transactions) satisfied by all rules.

    The minimum relative support value (#supporting transactions / #total transactions) satisfied by all rules.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  70. val miningSchema: MiningSchema
    Definition Classes
    AssociationModelHasMiningSchema
  71. def modelElement: ModelElement

    Model element type.

    Model element type.

    Definition Classes
    AssociationModelModel
  72. val modelExplanation: Option[ModelExplanation]
  73. 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
    HasWrappedModelAttributesHasModelAttributes
  74. val modelStats: Option[ModelStats]
    Definition Classes
    AssociationModelHasModelStats
  75. val modelVerification: Option[ModelVerification]
  76. def multiTargets: Boolean
    Definition Classes
    HasTargetFields
  77. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  78. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  79. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  80. lazy val nullSeries: Series

    A series with all null values is returned when can not produce a result.

    A series with all null values is returned when can not produce a result.

    Definition Classes
    Model
  81. def numClasses(name: String): Int

    Returns the number of class labels of the specified target.

    Returns the number of class labels of the specified target.

    Definition Classes
    Model
  82. lazy val numClasses: Int

    The number of class labels in a classification model.

    The number of class labels in a classification model.

    Definition Classes
    Model
  83. def numberOfItems: Int

    The number of different items contained in the input data.

    The number of different items contained in the input data. This number may be greater than or equal to the number of items contained in the model. The value will be greater if any items in the input data are excluded from the model, as a consequence of not being referenced by the model.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  84. def numberOfItemsets: Int

    The number of itemsets contained in the model.

    The number of itemsets contained in the model.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  85. def numberOfRules: Int

    The number of rules contained in the model.

    The number of rules contained in the model.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  86. def numberOfTransactions: Int

    The number of transactions contained in the input data.

    The number of transactions contained in the input data.

    Definition Classes
    HasWrappedAssociationAttributesHasAssociationAttributes
  87. def opType(name: String): OpType

    Returns optype of the specified target.

    Returns optype of the specified target.

    Definition Classes
    Model
  88. 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.

    Definition Classes
    Model
  89. val output: Option[Output]
    Definition Classes
    AssociationModelHasOutput
  90. def outputFields: Array[OutputField]
    Definition Classes
    HasOutput
  91. def outputIndex(feature: ResultFeature, value: Option[Any] = None): Int
    Definition Classes
    HasOutput
  92. def outputNames: Array[String]
    Definition Classes
    HasOutput
  93. def outputSchema: StructType

    The schema of final outputs.

    The schema of final outputs.

    Definition Classes
    Model
  94. var parent: Model

    The parent model.

    The parent model.

    Definition Classes
    AssociationModelHasParent
  95. def postClassification(name: String = null): (Any, Map[Any, Double])
    Attributes
    protected
    Definition Classes
    Model
  96. def postPredictedValue(outputs: MutablePredictedValue, name: String = null): MutablePredictedValue
    Attributes
    protected
    Definition Classes
    Model
  97. def postRegression(predictedValue: Any, name: String = null): Any
    Attributes
    protected
    Definition Classes
    Model
  98. def predict(values: Series): Series

    Predicts values for a given data series.

    Predicts values for a given data series.

    Definition Classes
    AssociationModelModelPredictable
  99. def predict(it: Iterator[Series]): Iterator[Series]
    Definition Classes
    Model
  100. 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

    Definition Classes
    Model
  101. def predict(values: List[Any]): List[Any]
    Definition Classes
    Model
  102. 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

    Predicts values for a given Array, and the order of those values is supposed as same as the input fields list

    Definition Classes
    Model
  103. def predict(values: (String, Any)*): Seq[(String, Any)]

    Predicts values for a given list of key/value pairs.

    Predicts values for a given list of key/value pairs.

    Definition Classes
    Model
  104. def predict(values: Map[String, Any]): Map[String, Any]

    Predicts values for a given data map of Java.

    Predicts values for a given data map of Java.

    Definition Classes
    Model
  105. def predict(values: Map[String, Any]): Map[String, Any]

    Predicts values for a given data map.

    Predicts values for a given data map.

    Definition Classes
    Model
  106. lazy val predictedValueIndex: Int
    Definition Classes
    HasOutput
  107. def prepare(series: Series): (Series, Boolean)

    Pre-process the input series.

    Pre-process the input series.

    Attributes
    protected
    Definition Classes
    Model
  108. def probabilitiesSupported: Boolean

    Tests if probabilities of categories of target can be produced by this model.

    Tests if probabilities of categories of target can be produced by this model.

    Definition Classes
    Model
  109. def result(series: Series, modelOutputs: ModelOutputs, fields: Array[OutputField] = Array.empty): Series
    Attributes
    protected
    Definition Classes
    Model
  110. def setOutputFields(outputFields: Array[OutputField]): AssociationModel.this.type
    Definition Classes
    HasOutput
  111. def setParent(parent: Model): AssociationModel.this.type
    Definition Classes
    HasParent
  112. def setSupplementOutput(value: Boolean): AssociationModel.this.type
    Definition Classes
    HasOutput
  113. def singleTarget: Boolean
    Definition Classes
    HasTargetFields
  114. def size: Int
    Definition Classes
    HasTargetFields
  115. 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
  116. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  117. lazy val targetClasses: Map[String, Array[Any]]

    The class labels of all categorical targets.

    The class labels of all categorical targets.

    Definition Classes
    Model
  118. lazy val targetField: Field

    The first target field for the supervised model.

    The first target field for the supervised model.

    Definition Classes
    Model
  119. 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.

    Definition Classes
    Model
  120. 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
  121. def targetName: String

    Name of the first target for the supervised model.

    Name of the first target for the supervised model.

    Definition Classes
    HasTargetFields
  122. lazy val targetNames: Array[String]

    All target names in an array.

    All target names in an array.

    Definition Classes
    ModelHasTargetFields
  123. def targetNamesOfResidual: Array[String]
    Definition Classes
    HasOutput
  124. val targets: Option[Targets]
    Definition Classes
    AssociationModelHasTargets
  125. def toString(): String
    Definition Classes
    AnyRef → Any
  126. def topCriteria: Map[(Algorithm, RankBasis, RankOrder), Int]
  127. def transformationDictionary: Option[TransformationDictionary]

    The optional transformation dictionary.

    The optional transformation dictionary.

    Definition Classes
    Model
  128. def unionCandidateOutputFields: Array[OutputField]
    Definition Classes
    HasOutput
  129. def unionOutputFields: Array[OutputField]
    Definition Classes
    HasOutput
  130. 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.

    Definition Classes
    Model
  131. lazy val usedSchema: StructType

    The schema of used fields.

    The schema of used fields.

    Definition Classes
    Model
  132. def version: String

    PMML version.

    PMML version.

    Definition Classes
    HasVersion
  133. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  134. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  135. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()

Inherited from Model

Inherited from PmmlElement

Inherited from Serializable

Inherited from HasExtensions

Inherited from HasModelVerification

Inherited from Predictable

Inherited from HasTargetFields

Inherited from ModelLocation

Inherited from FieldScope

Inherited from HasField

Inherited from HasTargets

Inherited from HasModelExplanation

Inherited from HasModelStats

Inherited from HasOutput

Inherited from HasMiningSchema

Inherited from HasModelAttributes

Inherited from HasVersion

Inherited from HasParent

Inherited from AnyRef

Inherited from Any

Ungrouped