Packages

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

Model produced by LightGBMRegressor.

Linear Supertypes
BasicLogging, ComplexParamsWritable, MLWritable, LightGBMPredictionParams, LightGBMModelMethods, LightGBMModelParams, Wrappable, RWrappable, PythonWrappable, BaseWrappable, RegressionModel[Vector, LightGBMRegressionModel], PredictionModel[Vector, LightGBMRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[LightGBMRegressionModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  2. By Inheritance
Inherited
  1. LightGBMRegressionModel
  2. BasicLogging
  3. ComplexParamsWritable
  4. MLWritable
  5. LightGBMPredictionParams
  6. LightGBMModelMethods
  7. LightGBMModelParams
  8. Wrappable
  9. RWrappable
  10. PythonWrappable
  11. BaseWrappable
  12. RegressionModel
  13. PredictionModel
  14. PredictorParams
  15. HasPredictionCol
  16. HasFeaturesCol
  17. HasLabelCol
  18. Model
  19. Transformer
  20. PipelineStage
  21. Logging
  22. Params
  23. Serializable
  24. Serializable
  25. Identifiable
  26. AnyRef
  27. Any
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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. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  16. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  17. def explainParams(): String
    Definition Classes
    Params
  18. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) ⇒ Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  19. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  20. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  21. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  22. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  23. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  24. 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
  25. val featuresShapCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  26. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  27. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  34. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  35. 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
  36. 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
  37. 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
  38. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  39. def getFeaturesShapCol: String
    Definition Classes
    LightGBMPredictionParams
  40. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  41. def getLeafPredictionCol: String
    Definition Classes
    LightGBMPredictionParams
  42. def getLightGBMBooster: LightGBMBooster
    Definition Classes
    LightGBMModelParams
  43. def getModel: LightGBMBooster

    Alias for same method

    Alias for same method

    returns

    The LightGBM Booster.

    Definition Classes
    LightGBMModelParams
  44. def getNumIterations: Int
    Definition Classes
    LightGBMModelParams
  45. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  46. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  47. def getPredictDisableShapeCheck: Boolean
    Definition Classes
    LightGBMPredictionParams
  48. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  49. 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
  50. def getStartIteration: Int
    Definition Classes
    LightGBMModelParams
  51. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  52. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  53. def hasParent: Boolean
    Definition Classes
    Model
  54. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  55. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  56. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  58. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  59. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  60. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  61. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  62. val leafPredictionCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  63. val lightGBMBooster: LightGBMBoosterParam
    Definition Classes
    LightGBMModelParams
  64. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  65. def logBase(methodName: String): Unit
    Attributes
    protected
    Definition Classes
    BasicLogging
  66. def logClass(): Unit
    Definition Classes
    BasicLogging
  67. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    BasicLogging
  72. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  73. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  76. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  77. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  80. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  81. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  82. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  85. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  86. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  87. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  88. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  89. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  90. val numIterations: IntParam
    Definition Classes
    LightGBMModelParams
  91. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  92. var parent: Estimator[LightGBMRegressionModel]
    Definition Classes
    Model
  93. def predict(features: Vector): Double
    Definition Classes
    LightGBMRegressionModel → PredictionModel
  94. val predictDisableShapeCheck: BooleanParam
    Definition Classes
    LightGBMPredictionParams
  95. 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
  96. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  97. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  98. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  99. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  100. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  101. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  102. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  103. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  104. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    LightGBMRegressionModel → PythonWrappable
  105. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  106. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  107. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  108. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  109. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  110. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  111. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  112. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  113. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  114. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  115. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  116. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  117. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  118. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  119. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  120. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  121. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  122. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  123. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  124. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  125. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  126. def saveNativeModel(filename: String, overwrite: Boolean): Unit
  127. final def set(paramPair: ParamPair[_]): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  128. final def set(param: String, value: Any): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  129. final def set[T](param: Param[T], value: T): LightGBMRegressionModel.this.type
    Definition Classes
    Params
  130. final def setDefault(paramPairs: ParamPair[_]*): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  131. final def setDefault[T](param: Param[T], value: T): LightGBMRegressionModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  132. def setFeaturesCol(value: String): LightGBMRegressionModel
    Definition Classes
    PredictionModel
  133. def setFeaturesShapCol(value: String): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMPredictionParams
  134. def setLeafPredictionCol(value: String): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMPredictionParams
  135. def setLightGBMBooster(value: LightGBMBooster): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMModelParams
  136. def setNumIterations(value: Int): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMModelParams
  137. def setParent(parent: Estimator[LightGBMRegressionModel]): LightGBMRegressionModel
    Definition Classes
    Model
  138. def setPredictDisableShapeCheck(value: Boolean): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMPredictionParams
  139. def setPredictionCol(value: String): LightGBMRegressionModel
    Definition Classes
    PredictionModel
  140. def setStartIteration(value: Int): LightGBMRegressionModel.this.type
    Definition Classes
    LightGBMModelParams
  141. val startIteration: IntParam
    Definition Classes
    LightGBMModelParams
  142. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  143. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  144. 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
  145. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  146. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  147. def transformImpl(dataset: Dataset[_]): DataFrame
    Attributes
    protected
    Definition Classes
    PredictionModel
  148. def transformSchema(schema: StructType): StructType
    Definition Classes
    PredictionModel → PipelineStage
  149. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  150. val uid: String
    Definition Classes
    LightGBMRegressionModel → BasicLogging → Identifiable
  151. def updateBoosterParamsBeforePredict(): Unit
    Attributes
    protected
    Definition Classes
    LightGBMModelMethods
  152. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    PredictorParams
  153. val ver: String
    Definition Classes
    BasicLogging
  154. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  155. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  156. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  157. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from BasicLogging

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from LightGBMPredictionParams

Inherited from LightGBMModelMethods

Inherited from LightGBMModelParams

Inherited from Wrappable

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