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

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. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  18. def dotnetClass(): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  19. lazy val dotnetClassName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  20. lazy val dotnetClassNameString: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  21. lazy val dotnetClassWrapperName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  22. lazy val dotnetCopyrightLines: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  23. def dotnetExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  24. def dotnetExtraMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  25. lazy val dotnetInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  26. def dotnetMLReadWriteMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  27. lazy val dotnetNamespace: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  28. lazy val dotnetObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  29. def dotnetParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  30. def dotnetParamGetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  31. def dotnetParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  32. def dotnetParamSetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  33. def dotnetWrapAsTypeMethod: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  34. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  35. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  36. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  37. def explainParams(): String
    Definition Classes
    Params
  38. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  39. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  40. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  41. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  42. 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
  43. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[OrthoForestDMLModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  44. def fit(dataset: Dataset[_], paramMap: ParamMap): OrthoForestDMLModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  45. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): OrthoForestDMLModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  46. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  47. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  48. def getConfidenceLevel: Double
    Definition Classes
    DoubleMLParams
  49. def getConfounderVecCol: String
    Definition Classes
    OrthoForestDMLParams
  50. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  51. def getExecutionContextProxy: ExecutionContext
    Definition Classes
    HasParallelismInjected
  52. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  53. def getHeterogeneityVecCol: String
    Definition Classes
    OrthoForestDMLParams
  54. def getMaxDepth: Int
    Definition Classes
    HasMaxDepth
  55. final def getMaxIter: Int
    Definition Classes
    HasMaxIter
  56. def getMinSamplesLeaf: Int
    Definition Classes
    HasMinSampleLeaf
  57. def getNumTrees: Int
    Definition Classes
    HasNumTrees
  58. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  59. def getOutcomeCol: String
    Definition Classes
    HasOutcomeCol
  60. def getOutcomeModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  61. def getOutcomeResidualCol: String
    Definition Classes
    OrthoForestDMLParams
  62. def getOutputCol: String

    Definition Classes
    HasOutputCol
  63. def getOutputHighCol: String
    Definition Classes
    OrthoForestDMLParams
  64. def getOutputLowCol: String
    Definition Classes
    OrthoForestDMLParams
  65. def getParallelism: Int
    Definition Classes
    HasParallelism
  66. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  67. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  68. def getSampleSplitRatio: Array[Double]
    Definition Classes
    DoubleMLParams
  69. def getTreatmentCol: String
    Definition Classes
    HasTreatmentCol
  70. def getTreatmentModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  71. def getTreatmentResidualCol: String
    Definition Classes
    OrthoForestDMLParams
  72. def getWeightCol: String

    Definition Classes
    HasWeightCol
  73. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  74. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  75. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  76. val heterogeneityVecCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  77. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  78. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  80. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  81. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  82. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  83. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  84. def logBase(info: SynapseMLLogInfo): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  85. def logBase(methodName: String, columns: Option[Int]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  86. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  87. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  88. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  89. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  90. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  91. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  92. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  93. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  94. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  95. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  96. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  97. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  98. def logTrain[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  99. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  100. def logVerb[T](verb: String, f: ⇒ T, columns: Int = -1): T
    Definition Classes
    SynapseMLLogging
  101. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  102. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  103. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  104. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  105. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  106. val maxDepth: IntParam
    Definition Classes
    HasMaxDepth
  107. final val maxIter: IntParam
    Definition Classes
    HasMaxIter
  108. val minSamplesLeaf: IntParam
    Definition Classes
    HasMinSampleLeaf
  109. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  110. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  111. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  112. val numTrees: IntParam
    Definition Classes
    HasNumTrees
  113. val outcomeCol: Param[String]
    Definition Classes
    HasOutcomeCol
  114. val outcomeModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  115. val outcomeResidualCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  116. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  117. val outputHighCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  118. val outputLowCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  119. val parallelism: IntParam
    Definition Classes
    HasParallelism
  120. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  121. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  122. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  123. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  124. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  125. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  126. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  127. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  128. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    PythonWrappable
  129. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  130. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  131. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  132. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  133. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  134. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  135. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  136. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  137. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  138. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  139. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  140. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  141. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  142. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  143. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  144. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  145. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  146. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  147. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  148. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  149. val sampleSplitRatio: DoubleArrayParam
    Definition Classes
    DoubleMLParams
  150. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  151. final def set(paramPair: ParamPair[_]): OrthoForestDMLEstimator.this.type
    Attributes
    protected
    Definition Classes
    Params
  152. final def set(param: String, value: Any): OrthoForestDMLEstimator.this.type
    Attributes
    protected
    Definition Classes
    Params
  153. final def set[T](param: Param[T], value: T): OrthoForestDMLEstimator.this.type
    Definition Classes
    Params
  154. 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
  155. def setConfounderVecCol(value: String): OrthoForestDMLEstimator.this.type

    Set confounder vector column

    Set confounder vector column

    Definition Classes
    OrthoForestDMLParams
  156. final def setDefault(paramPairs: ParamPair[_]*): OrthoForestDMLEstimator.this.type
    Attributes
    protected
    Definition Classes
    Params
  157. final def setDefault[T](param: Param[T], value: T): OrthoForestDMLEstimator.this.type
    Attributes
    protected
    Definition Classes
    Params
  158. def setFeaturesCol(value: String): OrthoForestDMLEstimator.this.type

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

    Set heterogeneity vector column

    Set heterogeneity vector column

    Definition Classes
    OrthoForestDMLParams
  160. 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
  161. 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
  162. 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
  163. 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
  164. 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
  165. 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
  166. def setOutcomeResidualCol(value: String): OrthoForestDMLEstimator.this.type

    Set outcome residual column

    Set outcome residual column

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

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

    Set output column for effect upper bound

    Set output column for effect upper bound

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

    Set output column for effect lower bound

    Set output column for effect lower bound

    Definition Classes
    OrthoForestDMLParams
  170. def setParallelism(value: Int): OrthoForestDMLEstimator.this.type
    Definition Classes
    DoubleMLParams
  171. 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
  172. 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
  173. 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
  174. def setTreatmentResidualCol(value: String): OrthoForestDMLEstimator.this.type

    Set treatment residual column

    Set treatment residual column

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

    Definition Classes
    HasWeightCol
  176. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  177. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  178. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  179. def transformSchema(schema: StructType): StructType
    Definition Classes
    OrthoForestDMLEstimator → PipelineStage
  180. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  181. val treatmentCol: Param[String]
    Definition Classes
    HasTreatmentCol
  182. val treatmentModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  183. val treatmentResidualCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  184. val uid: String
    Definition Classes
    OrthoForestDMLEstimator → SynapseMLLogging → Identifiable
  185. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  186. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  187. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  188. val weightCol: Param[String]

    The name of the weight column

    The name of the weight column

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

Inherited from SynapseMLLogging

Inherited from Wrappable

Inherited from DotnetWrappable

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