class DoubleMLModel extends Model[DoubleMLModel] with DoubleMLParams with ComplexParamsWritable with Wrappable with SynapseMLLogging

Model produced by DoubleMLEstimator.

Linear Supertypes
SynapseMLLogging, Wrappable, RWrappable, PythonWrappable, BaseWrappable, ComplexParamsWritable, MLWritable, DoubleMLParams, HasParallelismInjected, HasParallelism, HasWeightCol, HasMaxIter, HasFeaturesCol, HasOutcomeCol, HasTreatmentCol, Model[DoubleMLModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  2. By Inheritance
Inherited
  1. DoubleMLModel
  2. SynapseMLLogging
  3. Wrappable
  4. RWrappable
  5. PythonWrappable
  6. BaseWrappable
  7. ComplexParamsWritable
  8. MLWritable
  9. DoubleMLParams
  10. HasParallelismInjected
  11. HasParallelism
  12. HasWeightCol
  13. HasMaxIter
  14. HasFeaturesCol
  15. HasOutcomeCol
  16. HasTreatmentCol
  17. Model
  18. Transformer
  19. PipelineStage
  20. Logging
  21. Params
  22. Serializable
  23. Serializable
  24. Identifiable
  25. AnyRef
  26. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new DoubleMLModel()
  2. new DoubleMLModel(uid: String)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def awaitFutures[T](futures: Array[Future[T]]): Seq[T]
    Attributes
    protected
    Definition Classes
    HasParallelismInjected
  7. lazy val classNameHelper: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  8. final def clear(param: Param[_]): DoubleMLModel.this.type
    Definition Classes
    Params
  9. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  10. def companionModelClassName: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  11. val confidenceLevel: DoubleParam
    Definition Classes
    DoubleMLParams
  12. def copy(extra: ParamMap): DoubleMLModel
    Definition Classes
    DoubleMLModel → Model → Transformer → PipelineStage → Params
  13. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  14. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  15. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  16. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  17. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  18. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  19. def explainParams(): String
    Definition Classes
    Params
  20. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  21. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  22. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  23. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  24. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  25. def getAvgTreatmentEffect: Double
  26. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  27. def getConfidenceInterval: Array[Double]
  28. def getConfidenceLevel: Double
    Definition Classes
    DoubleMLParams
  29. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  30. def getExecutionContextProxy: ExecutionContext
    Definition Classes
    HasParallelismInjected
  31. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  32. final def getMaxIter: Int
    Definition Classes
    HasMaxIter
  33. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  34. def getOutcomeCol: String
    Definition Classes
    HasOutcomeCol
  35. def getOutcomeModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  36. def getPValue: Double
  37. def getParallelism: Int
    Definition Classes
    HasParallelism
  38. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  39. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  40. def getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  41. def getRawTreatmentEffects: Array[Double]
  42. def getSampleSplitRatio: Array[Double]
    Definition Classes
    DoubleMLParams
  43. def getTreatmentCol: String
    Definition Classes
    HasTreatmentCol
  44. def getTreatmentModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  45. def getWeightCol: String

    Definition Classes
    HasWeightCol
  46. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  47. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  48. def hasParent: Boolean
    Definition Classes
    Model
  49. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  50. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  51. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  52. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  53. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  54. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  55. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  56. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  57. def logBase(info: Map[String, String], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  58. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  59. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  60. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  65. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  66. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  69. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  72. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  73. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  76. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  77. final val maxIter: IntParam
    Definition Classes
    HasMaxIter
  78. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  79. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  80. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  81. val outcomeCol: Param[String]
    Definition Classes
    HasOutcomeCol
  82. val outcomeModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  83. val parallelism: IntParam
    Definition Classes
    HasParallelism
  84. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  85. var parent: Estimator[DoubleMLModel]
    Definition Classes
    Model
  86. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  87. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  88. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  89. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  90. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  91. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  92. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  93. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    DoubleMLModel → PythonWrappable
  94. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  95. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  96. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  97. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  98. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  99. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  100. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  101. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  102. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  103. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  104. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  105. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  106. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  107. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  108. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  109. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  110. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  111. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  112. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  113. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  114. val rawTreatmentEffects: DoubleArrayParam
  115. val sampleSplitRatio: DoubleArrayParam
    Definition Classes
    DoubleMLParams
  116. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  117. final def set(paramPair: ParamPair[_]): DoubleMLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  118. final def set(param: String, value: Any): DoubleMLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  119. final def set[T](param: Param[T], value: T): DoubleMLModel.this.type
    Definition Classes
    Params
  120. def setConfidenceLevel(value: Double): DoubleMLModel.this.type

    Set the higher bound percentile of ATE distribution.

    Set the higher bound percentile of ATE distribution. Default is 0.975. lower bound value will be automatically calculated as 100*(1-confidenceLevel) That means by default we compute 95% confidence interval, it is [2.5%, 97.5%] percentile of ATE distribution

    Definition Classes
    DoubleMLParams
  121. final def setDefault(paramPairs: ParamPair[_]*): DoubleMLModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  122. final def setDefault[T](param: Param[T], value: T): DoubleMLModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  123. def setFeaturesCol(value: String): DoubleMLModel.this.type

    Definition Classes
    HasFeaturesCol
  124. def setMaxIter(value: Int): DoubleMLModel.this.type

    Set the maximum number of confidence interval bootstrapping iterations.

    Set the maximum number of confidence interval bootstrapping iterations. Default is 1, which means it does not calculate confidence interval. To get Ci values please set a meaningful value

    Definition Classes
    DoubleMLParams
  125. def setOutcomeCol(value: String): DoubleMLModel.this.type

    Set name of the column which will be used as outcome

    Set name of the column which will be used as outcome

    Definition Classes
    HasOutcomeCol
  126. def setOutcomeModel(value: Estimator[_ <: Model[_]]): DoubleMLModel.this.type

    Set outcome model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Set outcome model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Definition Classes
    DoubleMLParams
  127. def setParallelism(value: Int): DoubleMLModel.this.type
    Definition Classes
    DoubleMLParams
  128. def setParent(parent: Estimator[DoubleMLModel]): DoubleMLModel
    Definition Classes
    Model
  129. def setRawTreatmentEffects(v: Array[Double]): DoubleMLModel.this.type
  130. def setSampleSplitRatio(value: Array[Double]): DoubleMLModel.this.type

    Set the sample split ratio, default is Array(0.5, 0.5)

    Set the sample split ratio, default is Array(0.5, 0.5)

    Definition Classes
    DoubleMLParams
  131. def setTreatmentCol(value: String): DoubleMLModel.this.type

    Set name of the column which will be used as treatment

    Set name of the column which will be used as treatment

    Definition Classes
    HasTreatmentCol
  132. def setTreatmentModel(value: Estimator[_ <: Model[_]]): DoubleMLModel.this.type

    Set treatment model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Set treatment model, it could be any model derived from 'org.apache.spark.ml.regression.Regressor' or 'org.apache.spark.ml.classification.ProbabilisticClassifier'

    Definition Classes
    DoubleMLParams
  133. def setWeightCol(value: String): DoubleMLModel.this.type

    Definition Classes
    HasWeightCol
  134. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  135. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  136. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  137. def transform(dataset: Dataset[_]): DataFrame

    :: Experimental :: DoubleMLEstimator transform function is still experimental, and its behavior could change in the future.

    :: Experimental :: DoubleMLEstimator transform function is still experimental, and its behavior could change in the future.

    Definition Classes
    DoubleMLModel → Transformer
    Annotations
    @Experimental()
  138. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  139. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  140. def transformSchema(schema: StructType): StructType
    Definition Classes
    DoubleMLModel → PipelineStage
    Annotations
    @DeveloperApi()
  141. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  142. val treatmentCol: Param[String]
    Definition Classes
    HasTreatmentCol
  143. val treatmentModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  144. val uid: String
    Definition Classes
    DoubleMLModel → SynapseMLLogging → Identifiable
  145. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  146. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  147. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  148. val weightCol: Param[String]

    The name of the weight column

    The name of the weight column

    Definition Classes
    HasWeightCol
  149. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

Inherited from Wrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from DoubleMLParams

Inherited from HasParallelismInjected

Inherited from HasParallelism

Inherited from HasWeightCol

Inherited from HasMaxIter

Inherited from HasFeaturesCol

Inherited from HasOutcomeCol

Inherited from HasTreatmentCol

Inherited from Model[DoubleMLModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

Ungrouped