class OrthoForestDMLEstimator extends Estimator[OrthoForestDMLModel] with ComplexParamsWritable with OrthoForestDMLParams with Wrappable with SynapseMLLogging with HasOutcomeCol

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Inherited
  1. OrthoForestDMLEstimator
  2. SynapseMLLogging
  3. Wrappable
  4. RWrappable
  5. PythonWrappable
  6. BaseWrappable
  7. OrthoForestDMLParams
  8. HasOutputCol
  9. HasMinSampleLeaf
  10. HasMaxDepth
  11. HasNumTrees
  12. DoubleMLParams
  13. HasParallelismInjected
  14. HasParallelism
  15. HasWeightCol
  16. HasMaxIter
  17. HasFeaturesCol
  18. HasOutcomeCol
  19. HasTreatmentCol
  20. ComplexParamsWritable
  21. MLWritable
  22. Estimator
  23. PipelineStage
  24. Logging
  25. Params
  26. Serializable
  27. Serializable
  28. Identifiable
  29. AnyRef
  30. Any
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Visibility
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Instance Constructors

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

Type Members

  1. type EstimatorWithPC = Estimator[_ <: Model[_] with HasPredictionCol] with HasPredictionCol

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[_]): OrthoForestDMLEstimator.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. val confounderVecCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  13. def copy(extra: ParamMap): Estimator[OrthoForestDMLModel]
    Definition Classes
    OrthoForestDMLEstimator → Estimator → PipelineStage → Params
  14. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  15. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  16. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  17. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  19. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  20. def explainParams(): String
    Definition Classes
    Params
  21. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  22. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  23. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  24. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  25. def fit(dataset: Dataset[_]): OrthoForestDMLModel

    Fits the OrthoForestDML model.

    Fits the OrthoForestDML model.

    dataset

    The input dataset to train.

    returns

    The trained DoubleML model, from which you can get Ate and Ci values

    Definition Classes
    OrthoForestDMLEstimator → Estimator
  26. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[OrthoForestDMLModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  27. def fit(dataset: Dataset[_], paramMap: ParamMap): OrthoForestDMLModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  28. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): OrthoForestDMLModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  29. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  30. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  31. def getConfidenceLevel: Double
    Definition Classes
    DoubleMLParams
  32. def getConfounderVecCol: String
    Definition Classes
    OrthoForestDMLParams
  33. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  34. def getExecutionContextProxy: ExecutionContext
    Definition Classes
    HasParallelismInjected
  35. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  36. def getHeterogeneityVecCol: String
    Definition Classes
    OrthoForestDMLParams
  37. def getMaxDepth: Int
    Definition Classes
    HasMaxDepth
  38. final def getMaxIter: Int
    Definition Classes
    HasMaxIter
  39. def getMinSamplesLeaf: Int
    Definition Classes
    HasMinSampleLeaf
  40. def getNumTrees: Int
    Definition Classes
    HasNumTrees
  41. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  42. def getOutcomeCol: String
    Definition Classes
    HasOutcomeCol
  43. def getOutcomeModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  44. def getOutcomeResidualCol: String
    Definition Classes
    OrthoForestDMLParams
  45. def getOutputCol: String

    Definition Classes
    HasOutputCol
  46. def getOutputHighCol: String
    Definition Classes
    OrthoForestDMLParams
  47. def getOutputLowCol: String
    Definition Classes
    OrthoForestDMLParams
  48. def getParallelism: Int
    Definition Classes
    HasParallelism
  49. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  50. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  51. def getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  52. def getSampleSplitRatio: Array[Double]
    Definition Classes
    DoubleMLParams
  53. def getTreatmentCol: String
    Definition Classes
    HasTreatmentCol
  54. def getTreatmentModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  55. def getTreatmentResidualCol: String
    Definition Classes
    OrthoForestDMLParams
  56. def getWeightCol: String

    Definition Classes
    HasWeightCol
  57. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  58. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  59. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  60. val heterogeneityVecCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  61. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  62. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  64. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  65. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  66. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  67. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  68. def logBase(info: Map[String, String], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  69. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  70. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  71. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  76. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  77. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  80. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  81. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  83. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  84. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  85. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  87. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  88. val maxDepth: IntParam
    Definition Classes
    HasMaxDepth
  89. final val maxIter: IntParam
    Definition Classes
    HasMaxIter
  90. val minSamplesLeaf: IntParam
    Definition Classes
    HasMinSampleLeaf
  91. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  92. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  93. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  94. val numTrees: IntParam
    Definition Classes
    HasNumTrees
  95. val outcomeCol: Param[String]
    Definition Classes
    HasOutcomeCol
  96. val outcomeModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  97. val outcomeResidualCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  98. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  99. val outputHighCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  100. val outputLowCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  101. val parallelism: IntParam
    Definition Classes
    HasParallelism
  102. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  103. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  104. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  105. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  106. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  107. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  108. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  109. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  110. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    PythonWrappable
  111. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  112. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  113. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  114. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  115. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  116. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  117. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  118. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  119. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  120. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  121. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  122. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  123. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  124. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  125. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  126. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  127. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  128. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  129. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  130. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  131. val sampleSplitRatio: DoubleArrayParam
    Definition Classes
    DoubleMLParams
  132. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  133. final def set(paramPair: ParamPair[_]): OrthoForestDMLEstimator.this.type
    Attributes
    protected
    Definition Classes
    Params
  134. final def set(param: String, value: Any): OrthoForestDMLEstimator.this.type
    Attributes
    protected
    Definition Classes
    Params
  135. final def set[T](param: Param[T], value: T): OrthoForestDMLEstimator.this.type
    Definition Classes
    Params
  136. def setConfidenceLevel(value: Double): OrthoForestDMLEstimator.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
  137. def setConfounderVecCol(value: String): OrthoForestDMLEstimator.this.type

    Set confounder vector column

    Set confounder vector column

    Definition Classes
    OrthoForestDMLParams
  138. final def setDefault(paramPairs: ParamPair[_]*): OrthoForestDMLEstimator.this.type
    Attributes
    protected
    Definition Classes
    Params
  139. final def setDefault[T](param: Param[T], value: T): OrthoForestDMLEstimator.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  140. def setFeaturesCol(value: String): OrthoForestDMLEstimator.this.type

    Definition Classes
    HasFeaturesCol
  141. def setHeterogeneityVecCol(value: String): OrthoForestDMLEstimator.this.type

    Set heterogeneity vector column

    Set heterogeneity vector column

    Definition Classes
    OrthoForestDMLParams
  142. def setMaxDepth(value: Int): OrthoForestDMLEstimator.this.type

    Set max depth of the trees to be used in the forest

    Set max depth of the trees to be used in the forest

    Definition Classes
    HasMaxDepth
  143. def setMaxIter(value: Int): OrthoForestDMLEstimator.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
  144. def setMinSamplesLeaf(value: Int): OrthoForestDMLEstimator.this.type

    Set number of samples in the leaf node of trees to be used in the forest

    Set number of samples in the leaf node of trees to be used in the forest

    Definition Classes
    HasMinSampleLeaf
  145. def setNumTrees(value: Int): OrthoForestDMLEstimator.this.type

    Set number of trees to be used in the forest

    Set number of trees to be used in the forest

    Definition Classes
    HasNumTrees
  146. def setOutcomeCol(value: String): OrthoForestDMLEstimator.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
  147. def setOutcomeModel(value: Estimator[_ <: Model[_]]): OrthoForestDMLEstimator.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
  148. def setOutcomeResidualCol(value: String): OrthoForestDMLEstimator.this.type

    Set outcome residual column

    Set outcome residual column

    Definition Classes
    OrthoForestDMLParams
  149. def setOutputCol(value: String): OrthoForestDMLEstimator.this.type

    Definition Classes
    HasOutputCol
  150. def setOutputHighCol(value: String): OrthoForestDMLEstimator.this.type

    Set output column for effect upper bound

    Set output column for effect upper bound

    Definition Classes
    OrthoForestDMLParams
  151. def setOutputLowCol(value: String): OrthoForestDMLEstimator.this.type

    Set output column for effect lower bound

    Set output column for effect lower bound

    Definition Classes
    OrthoForestDMLParams
  152. def setParallelism(value: Int): OrthoForestDMLEstimator.this.type
    Definition Classes
    DoubleMLParams
  153. def setSampleSplitRatio(value: Array[Double]): OrthoForestDMLEstimator.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
  154. def setTreatmentCol(value: String): OrthoForestDMLEstimator.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
  155. def setTreatmentModel(value: Estimator[_ <: Model[_]]): OrthoForestDMLEstimator.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
  156. def setTreatmentResidualCol(value: String): OrthoForestDMLEstimator.this.type

    Set treatment residual column

    Set treatment residual column

    Definition Classes
    OrthoForestDMLParams
  157. def setWeightCol(value: String): OrthoForestDMLEstimator.this.type

    Definition Classes
    HasWeightCol
  158. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  159. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  160. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  161. def transformSchema(schema: StructType): StructType
    Definition Classes
    OrthoForestDMLEstimator → PipelineStage
  162. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  163. val treatmentCol: Param[String]
    Definition Classes
    HasTreatmentCol
  164. val treatmentModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  165. val treatmentResidualCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  166. val uid: String
    Definition Classes
    OrthoForestDMLEstimator → SynapseMLLogging → Identifiable
  167. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  168. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  169. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  170. val weightCol: Param[String]

    The name of the weight column

    The name of the weight column

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

Inherited from SynapseMLLogging

Inherited from Wrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from OrthoForestDMLParams

Inherited from HasOutputCol

Inherited from HasMinSampleLeaf

Inherited from HasMaxDepth

Inherited from HasNumTrees

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 ComplexParamsWritable

Inherited from MLWritable

Inherited from Estimator[OrthoForestDMLModel]

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