class LightGBMRegressionModel extends RegressionModel[Vector, LightGBMRegressionModel] with LightGBMModelParams with LightGBMModelMethods with LightGBMPredictionParams with ComplexParamsWritable with SynapseMLLogging

Model produced by LightGBMRegressor.

Linear Supertypes
SynapseMLLogging, ComplexParamsWritable, MLWritable, LightGBMPredictionParams, LightGBMModelMethods, LightGBMModelParams, Wrappable, DotnetWrappable, RWrappable, PythonWrappable, BaseWrappable, RegressionModel[Vector, LightGBMRegressionModel], PredictionModel[Vector, LightGBMRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[LightGBMRegressionModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. LightGBMRegressionModel
  2. SynapseMLLogging
  3. ComplexParamsWritable
  4. MLWritable
  5. LightGBMPredictionParams
  6. LightGBMModelMethods
  7. LightGBMModelParams
  8. Wrappable
  9. DotnetWrappable
  10. RWrappable
  11. PythonWrappable
  12. BaseWrappable
  13. RegressionModel
  14. PredictionModel
  15. PredictorParams
  16. HasPredictionCol
  17. HasFeaturesCol
  18. HasLabelCol
  19. Model
  20. Transformer
  21. PipelineStage
  22. Logging
  23. Params
  24. Serializable
  25. Serializable
  26. Identifiable
  27. AnyRef
  28. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new LightGBMRegressionModel()
  2. new LightGBMRegressionModel(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. lazy val classNameHelper: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  7. final def clear(param: Param[_]): LightGBMRegressionModel.this.type
    Definition Classes
    Params
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  9. def companionModelClassName: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  10. def copy(extra: ParamMap): LightGBMRegressionModel
    Definition Classes
    LightGBMRegressionModel → Model → Transformer → PipelineStage → Params
  11. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  12. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  13. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  14. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  15. def dotnetClass(): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  16. lazy val dotnetClassName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  17. lazy val dotnetClassNameString: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  18. lazy val dotnetClassWrapperName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  19. lazy val dotnetCopyrightLines: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  20. def dotnetExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  21. def dotnetExtraMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  22. lazy val dotnetInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  23. def dotnetMLReadWriteMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  24. lazy val dotnetNamespace: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  25. lazy val dotnetObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  26. def dotnetParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  27. def dotnetParamGetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  28. def dotnetParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  29. def dotnetParamSetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  30. def dotnetWrapAsTypeMethod: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  31. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  32. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  33. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  34. def explainParams(): String
    Definition Classes
    Params
  35. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) ⇒ Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  36. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  37. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  38. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  39. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  40. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  41. def featuresShap(features: Vector): Vector

    Protected method to predict local SHAP feature importance values for an instance.

    Protected method to predict local SHAP feature importance values for an instance.

    features

    The local instance or row to compute the local SHAP values for.

    returns

    The SHAP local feature importance values.

    Attributes
    protected
    Definition Classes
    LightGBMModelMethods
  42. val featuresShapCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  43. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  44. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  45. def getBoosterBestIteration(): Int

    Public method to get the best iteration from the booster.

    Public method to get the best iteration from the booster.

    returns

    The best iteration, if early stopping was triggered.

    Definition Classes
    LightGBMModelMethods
  46. def getBoosterNumClasses(): Int

    Public method to get the number of classes from the booster.

    Public method to get the number of classes from the booster.

    returns

    The number of classes.

    Definition Classes
    LightGBMModelMethods
  47. def getBoosterNumFeatures(): Int

    Public method to get the number of features from the booster.

    Public method to get the number of features from the booster.

    returns

    The number of features.

    Definition Classes
    LightGBMModelMethods
  48. def getBoosterNumTotalIterations(): Int

    Public method to get the total number of iterations trained.

    Public method to get the total number of iterations trained.

    returns

    The total number of iterations trained.

    Definition Classes
    LightGBMModelMethods
  49. def getBoosterNumTotalModel(): Int

    Public method to get the total number of models trained.

    Public method to get the total number of models trained. Note this may be larger than the number of iterations, since in multiclass a model is trained per class for each iteration.

    returns

    The total number of models.

    Definition Classes
    LightGBMModelMethods
  50. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  51. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  52. def getDenseFeatureShaps(features: Array[Double]): Array[Double]

    Public method for pyspark API to get the dense local SHAP feature importance values for an instance.

    Public method for pyspark API to get the dense local SHAP feature importance values for an instance.

    features

    The local instance or row to compute the SHAP values for.

    returns

    The local feature importance values.

    Definition Classes
    LightGBMModelMethods
  53. def getFeatureImportances(importanceType: String): Array[Double]

    Public method to get the global feature importance values.

    Public method to get the global feature importance values.

    importanceType

    split or gini

    returns

    The global feature importance values.

    Definition Classes
    LightGBMModelMethods
  54. def getFeatureShaps(features: Vector): Array[Double]

    Public method to get the vector local SHAP feature importance values for an instance.

    Public method to get the vector local SHAP feature importance values for an instance.

    features

    The local instance or row to compute the SHAP values for.

    returns

    The local feature importance values.

    Definition Classes
    LightGBMModelMethods
  55. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  56. def getFeaturesShapCol: String
    Definition Classes
    LightGBMPredictionParams
  57. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  58. def getLeafPredictionCol: String
    Definition Classes
    LightGBMPredictionParams
  59. def getLightGBMBooster: LightGBMBooster
    Definition Classes
    LightGBMModelParams
  60. def getModel: LightGBMBooster

    Alias for same method

    Alias for same method

    returns

    The LightGBM Booster.

    Definition Classes
    LightGBMModelParams
  61. def getNativeModel(): String

    Gets the native model serialized representation as a string.

    Gets the native model serialized representation as a string.

    Definition Classes
    LightGBMModelMethods
  62. def getNumIterations: Int
    Definition Classes
    LightGBMModelParams
  63. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  64. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  65. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  66. def getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  67. def getPredictDisableShapeCheck: Boolean
    Definition Classes
    LightGBMPredictionParams
  68. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  69. def getSparseFeatureShaps(size: Int, indices: Array[Int], values: Array[Double]): Array[Double]

    Public method for pyspark API to get the sparse local SHAP feature importance values for an instance.

    Public method for pyspark API to get the sparse local SHAP feature importance values for an instance.

    returns

    The local feature importance values.

    Definition Classes
    LightGBMModelMethods
  70. def getStartIteration: Int
    Definition Classes
    LightGBMModelParams
  71. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  72. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  73. def hasParent: Boolean
    Definition Classes
    Model
  74. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  75. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  76. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  78. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  79. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  80. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  81. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  82. val leafPredictionCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  83. val lightGBMBooster: LightGBMBoosterParam
    Definition Classes
    LightGBMModelParams
  84. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  85. def logBase(info: Map[String, String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  86. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  87. def logClass(): Unit
    Definition Classes
    SynapseMLLogging
  88. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  89. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  90. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  91. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  92. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  93. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  94. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  95. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  96. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  97. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  98. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  99. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  100. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): 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. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  107. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  108. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  109. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  110. val numIterations: IntParam
    Definition Classes
    LightGBMModelParams
  111. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  112. var parent: Estimator[LightGBMRegressionModel]
    Definition Classes
    Model
  113. def predict(features: Vector): Double
    Definition Classes
    LightGBMRegressionModel → PredictionModel
  114. val predictDisableShapeCheck: BooleanParam
    Definition Classes
    LightGBMPredictionParams
  115. def predictLeaf(features: Vector): Vector

    Protected method to predict leaf index.

    Protected method to predict leaf index.

    features

    The local instance or row to compute the leaf index for.

    returns

    The predicted leaf index.

    Attributes
    protected
    Definition Classes
    LightGBMModelMethods
  116. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  117. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  118. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  119. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  120. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  121. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  122. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  123. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  124. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    LightGBMRegressionModel → PythonWrappable
  125. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  126. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  127. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  128. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  129. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  130. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  131. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  132. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  133. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  134. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  135. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  136. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  137. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  138. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  139. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  140. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  141. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  142. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  143. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  144. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  145. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  146. def saveNativeModel(filename: String, overwrite: Boolean): Unit

    Saves the native model serialized representation to file.

    Saves the native model serialized representation to file.

    filename

    The name of the file to save the model to

    overwrite

    Whether to overwrite if the file already exists

    Definition Classes
    LightGBMModelMethods
  147. final def set(paramPair: ParamPair[_]): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  148. final def set(param: String, value: Any): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  149. final def set[T](param: Param[T], value: T): LightGBMRegressionModel.this.type
    Definition Classes
    Params
  150. final def setDefault(paramPairs: ParamPair[_]*): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  151. final def setDefault[T](param: Param[T], value: T): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  152. def setFeaturesCol(value: String): LightGBMRegressionModel
    Definition Classes
    PredictionModel
  153. def setFeaturesShapCol(value: String): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMPredictionParams
  154. def setLeafPredictionCol(value: String): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMPredictionParams
  155. def setLightGBMBooster(value: LightGBMBooster): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMModelParams
  156. def setNumIterations(value: Int): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMModelParams
  157. def setParent(parent: Estimator[LightGBMRegressionModel]): LightGBMRegressionModel
    Definition Classes
    Model
  158. def setPredictDisableShapeCheck(value: Boolean): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMPredictionParams
  159. def setPredictionCol(value: String): LightGBMRegressionModel
    Definition Classes
    PredictionModel
  160. def setStartIteration(value: Int): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMModelParams
  161. val startIteration: IntParam
    Definition Classes
    LightGBMModelParams
  162. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  163. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  164. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  165. def transform(dataset: Dataset[_]): DataFrame

    Adds additional Leaf Index and SHAP columns if specified.

    Adds additional Leaf Index and SHAP columns if specified.

    dataset

    input dataset

    returns

    transformed dataset

    Definition Classes
    LightGBMRegressionModel → PredictionModel → Transformer
  166. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  167. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  168. def transformImpl(dataset: Dataset[_]): DataFrame
    Attributes
    protected
    Definition Classes
    PredictionModel
  169. def transformSchema(schema: StructType): StructType
    Definition Classes
    PredictionModel → PipelineStage
  170. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  171. val uid: String
    Definition Classes
    LightGBMRegressionModel → SynapseMLLogging → Identifiable
  172. def updateBoosterParamsBeforePredict(): Unit
    Attributes
    protected
    Definition Classes
    LightGBMModelMethods
  173. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    PredictorParams
  174. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  175. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  176. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  177. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from LightGBMPredictionParams

Inherited from LightGBMModelMethods

Inherited from LightGBMModelParams

Inherited from Wrappable

Inherited from DotnetWrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from RegressionModel[Vector, LightGBMRegressionModel]

Inherited from PredictionModel[Vector, LightGBMRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[LightGBMRegressionModel]

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

Ungrouped