class OrthoForestDMLModel extends Model[OrthoForestDMLModel] with OrthoForestDMLParams with ComplexParamsWritable with Wrappable with SynapseMLLogging

Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. OrthoForestDMLModel
  2. SynapseMLLogging
  3. Wrappable
  4. DotnetWrappable
  5. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. ComplexParamsWritable
  9. MLWritable
  10. OrthoForestDMLParams
  11. HasOutputCol
  12. HasMinSampleLeaf
  13. HasMaxDepth
  14. HasNumTrees
  15. DoubleMLParams
  16. HasParallelismInjected
  17. HasParallelism
  18. HasWeightCol
  19. HasMaxIter
  20. HasFeaturesCol
  21. HasOutcomeCol
  22. HasTreatmentCol
  23. Model
  24. Transformer
  25. PipelineStage
  26. Logging
  27. Params
  28. Serializable
  29. Serializable
  30. Identifiable
  31. AnyRef
  32. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

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

Value Members

  1. final def clear(param: Param[_]): OrthoForestDMLModel.this.type
    Definition Classes
    Params
  2. val confidenceLevel: DoubleParam
    Definition Classes
    DoubleMLParams
  3. val confounderVecCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  4. def copy(extra: ParamMap): OrthoForestDMLModel
    Definition Classes
    OrthoForestDMLModel → Model → Transformer → PipelineStage → Params
  5. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  6. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  7. def explainParams(): String
    Definition Classes
    Params
  8. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  9. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  10. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  11. val forest: TransformerArrayParam
  12. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  13. def getConfidenceLevel: Double
    Definition Classes
    DoubleMLParams
  14. def getConfounderVecCol: String
    Definition Classes
    OrthoForestDMLParams
  15. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  16. def getExecutionContextProxy: ExecutionContext
    Definition Classes
    HasParallelismInjected
  17. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  18. def getHeterogeneityVecCol: String
    Definition Classes
    OrthoForestDMLParams
  19. def getMaxDepth: Int
    Definition Classes
    HasMaxDepth
  20. final def getMaxIter: Int
    Definition Classes
    HasMaxIter
  21. def getMinSamplesLeaf: Int
    Definition Classes
    HasMinSampleLeaf
  22. def getNumTrees: Int
    Definition Classes
    HasNumTrees
  23. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  24. def getOutcomeCol: String
    Definition Classes
    HasOutcomeCol
  25. def getOutcomeModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  26. def getOutcomeResidualCol: String
    Definition Classes
    OrthoForestDMLParams
  27. def getOutputCol: String

    Definition Classes
    HasOutputCol
  28. def getOutputHighCol: String
    Definition Classes
    OrthoForestDMLParams
  29. def getOutputLowCol: String
    Definition Classes
    OrthoForestDMLParams
  30. def getParallelism: Int
    Definition Classes
    HasParallelism
  31. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  32. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  33. def getSampleSplitRatio: Array[Double]
    Definition Classes
    DoubleMLParams
  34. def getTreatmentCol: String
    Definition Classes
    HasTreatmentCol
  35. def getTreatmentModel: Estimator[_ <: Model[_]]
    Definition Classes
    DoubleMLParams
  36. def getTreatmentResidualCol: String
    Definition Classes
    OrthoForestDMLParams
  37. def getWeightCol: String

    Definition Classes
    HasWeightCol
  38. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  39. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  40. def hasParent: Boolean
    Definition Classes
    Model
  41. val heterogeneityVecCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  42. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  43. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  44. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  45. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  46. def logTrain[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  47. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  48. def logVerb[T](verb: String, f: ⇒ T, columns: Int = -1): T
    Definition Classes
    SynapseMLLogging
  49. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  50. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  51. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  52. val maxDepth: IntParam
    Definition Classes
    HasMaxDepth
  53. final val maxIter: IntParam
    Definition Classes
    HasMaxIter
  54. val minSamplesLeaf: IntParam
    Definition Classes
    HasMinSampleLeaf
  55. val numTrees: IntParam
    Definition Classes
    HasNumTrees
  56. val outcomeCol: Param[String]
    Definition Classes
    HasOutcomeCol
  57. val outcomeModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  58. val outcomeResidualCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  59. val outputCol: Param[String]

    The name of the output column

    The name of the output column

    Definition Classes
    HasOutputCol
  60. val outputHighCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  61. val outputLowCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  62. val parallelism: IntParam
    Definition Classes
    HasParallelism
  63. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  64. var parent: Estimator[OrthoForestDMLModel]
    Definition Classes
    Model
  65. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  66. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  67. val sampleSplitRatio: DoubleArrayParam
    Definition Classes
    DoubleMLParams
  68. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  69. final def set[T](param: Param[T], value: T): OrthoForestDMLModel.this.type
    Definition Classes
    Params
  70. def setConfidenceLevel(value: Double): OrthoForestDMLModel.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
  71. def setConfounderVecCol(value: String): OrthoForestDMLModel.this.type

    Set confounder vector column

    Set confounder vector column

    Definition Classes
    OrthoForestDMLParams
  72. def setFeaturesCol(value: String): OrthoForestDMLModel.this.type

    Definition Classes
    HasFeaturesCol
  73. def setForest(v: Array[DecisionTreeRegressionModel]): OrthoForestDMLModel.this.type
  74. def setHeterogeneityVecCol(value: String): OrthoForestDMLModel.this.type

    Set heterogeneity vector column

    Set heterogeneity vector column

    Definition Classes
    OrthoForestDMLParams
  75. def setMaxDepth(value: Int): OrthoForestDMLModel.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
  76. def setMaxIter(value: Int): OrthoForestDMLModel.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
  77. def setMinSamplesLeaf(value: Int): OrthoForestDMLModel.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
  78. def setNumTrees(value: Int): OrthoForestDMLModel.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
  79. def setOutcomeCol(value: String): OrthoForestDMLModel.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
  80. def setOutcomeModel(value: Estimator[_ <: Model[_]]): OrthoForestDMLModel.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
  81. def setOutcomeResidualCol(value: String): OrthoForestDMLModel.this.type

    Set outcome residual column

    Set outcome residual column

    Definition Classes
    OrthoForestDMLParams
  82. def setOutputCol(value: String): OrthoForestDMLModel.this.type

    Definition Classes
    HasOutputCol
  83. def setOutputHighCol(value: String): OrthoForestDMLModel.this.type

    Set output column for effect upper bound

    Set output column for effect upper bound

    Definition Classes
    OrthoForestDMLParams
  84. def setOutputLowCol(value: String): OrthoForestDMLModel.this.type

    Set output column for effect lower bound

    Set output column for effect lower bound

    Definition Classes
    OrthoForestDMLParams
  85. def setParallelism(value: Int): OrthoForestDMLModel.this.type
    Definition Classes
    DoubleMLParams
  86. def setParent(parent: Estimator[OrthoForestDMLModel]): OrthoForestDMLModel
    Definition Classes
    Model
  87. def setSampleSplitRatio(value: Array[Double]): OrthoForestDMLModel.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
  88. def setTreatmentCol(value: String): OrthoForestDMLModel.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
  89. def setTreatmentModel(value: Estimator[_ <: Model[_]]): OrthoForestDMLModel.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
  90. def setTreatmentResidualCol(value: String): OrthoForestDMLModel.this.type

    Set treatment residual column

    Set treatment residual column

    Definition Classes
    OrthoForestDMLParams
  91. def setWeightCol(value: String): OrthoForestDMLModel.this.type

    Definition Classes
    HasWeightCol
  92. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  93. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    OrthoForestDMLModel → Transformer
  94. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  95. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  96. def transformSchema(schema: StructType): StructType
    Definition Classes
    OrthoForestDMLModel → PipelineStage
  97. val treatmentCol: Param[String]
    Definition Classes
    HasTreatmentCol
  98. val treatmentModel: EstimatorParam
    Definition Classes
    DoubleMLParams
  99. val treatmentResidualCol: Param[String]
    Definition Classes
    OrthoForestDMLParams
  100. val uid: String
    Definition Classes
    OrthoForestDMLModel → SynapseMLLogging → Identifiable
  101. val weightCol: Param[String]

    The name of the weight column

    The name of the weight column

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