Packages

class LightGBMClassificationModel extends ProbabilisticClassificationModel[Vector, LightGBMClassificationModel] with LightGBMModelParams with LightGBMModelMethods with LightGBMPredictionParams with HasActualNumClasses with ComplexParamsWritable with BasicLogging

Model produced by LightGBMClassifier.

Linear Supertypes
BasicLogging, ComplexParamsWritable, MLWritable, HasActualNumClasses, LightGBMPredictionParams, LightGBMModelMethods, LightGBMModelParams, Wrappable, RWrappable, PythonWrappable, BaseWrappable, ProbabilisticClassificationModel[Vector, LightGBMClassificationModel], ProbabilisticClassifierParams, HasThresholds, HasProbabilityCol, ClassificationModel[Vector, LightGBMClassificationModel], ClassifierParams, HasRawPredictionCol, PredictionModel[Vector, LightGBMClassificationModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[LightGBMClassificationModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. LightGBMClassificationModel
  2. BasicLogging
  3. ComplexParamsWritable
  4. MLWritable
  5. HasActualNumClasses
  6. LightGBMPredictionParams
  7. LightGBMModelMethods
  8. LightGBMModelParams
  9. Wrappable
  10. RWrappable
  11. PythonWrappable
  12. BaseWrappable
  13. ProbabilisticClassificationModel
  14. ProbabilisticClassifierParams
  15. HasThresholds
  16. HasProbabilityCol
  17. ClassificationModel
  18. ClassifierParams
  19. HasRawPredictionCol
  20. PredictionModel
  21. PredictorParams
  22. HasPredictionCol
  23. HasFeaturesCol
  24. HasLabelCol
  25. Model
  26. Transformer
  27. PipelineStage
  28. Logging
  29. Params
  30. Serializable
  31. Serializable
  32. Identifiable
  33. AnyRef
  34. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new LightGBMClassificationModel()
  2. new LightGBMClassificationModel(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. val actualNumClasses: IntParam
    Definition Classes
    HasActualNumClasses
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. lazy val classNameHelper: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  8. final def clear(param: Param[_]): LightGBMClassificationModel.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. def copy(extra: ParamMap): LightGBMClassificationModel
    Definition Classes
    LightGBMClassificationModel → Model → Transformer → PipelineStage → Params
  12. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  13. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  14. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  15. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  16. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  17. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  18. def explainParams(): String
    Definition Classes
    Params
  19. def extractInstances(dataset: Dataset[_], numClasses: Int): RDD[Instance]
    Attributes
    protected
    Definition Classes
    ClassifierParams
  20. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) ⇒ Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  21. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  22. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  23. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  24. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  25. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  26. 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
  27. val featuresShapCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  28. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  29. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  30. def getActualNumClasses: Int
    Definition Classes
    HasActualNumClasses
  31. 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
  32. 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
  33. 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
  34. 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
  35. 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
  36. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  37. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  38. 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
  39. 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
  40. 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
  41. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  42. def getFeaturesShapCol: String
    Definition Classes
    LightGBMPredictionParams
  43. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  44. def getLeafPredictionCol: String
    Definition Classes
    LightGBMPredictionParams
  45. def getLightGBMBooster: LightGBMBooster
    Definition Classes
    LightGBMModelParams
  46. def getModel: LightGBMBooster

    Alias for same method

    Alias for same method

    returns

    The LightGBM Booster.

    Definition Classes
    LightGBMModelParams
  47. def getNumIterations: Int
    Definition Classes
    LightGBMModelParams
  48. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  49. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  50. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  51. final def getProbabilityCol: String
    Definition Classes
    HasProbabilityCol
  52. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  53. 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
  54. def getStartIteration: Int
    Definition Classes
    LightGBMModelParams
  55. def getThresholds: Array[Double]
    Definition Classes
    HasThresholds
  56. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  57. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  58. def hasParent: Boolean
    Definition Classes
    Model
  59. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  60. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  61. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  63. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  64. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  65. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  66. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  67. val leafPredictionCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  68. val lightGBMBooster: LightGBMBoosterParam
    Definition Classes
    LightGBMModelParams
  69. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  70. def logBase(methodName: String): Unit
    Attributes
    protected
    Definition Classes
    BasicLogging
  71. def logClass(): Unit
    Definition Classes
    BasicLogging
  72. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    BasicLogging
  77. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  78. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  81. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  82. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  84. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  85. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  86. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  87. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  88. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  89. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  90. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  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. def numClasses: Int
    Definition Classes
    LightGBMClassificationModel → ClassificationModel
  95. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  96. val numIterations: IntParam
    Definition Classes
    LightGBMModelParams
  97. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  98. var parent: Estimator[LightGBMClassificationModel]
    Definition Classes
    Model
  99. def predict(features: Vector): Double
    Definition Classes
    ClassificationModel → PredictionModel
  100. def predictColumn: Column
    Attributes
    protected
  101. 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
  102. def predictProbability(features: Vector): Vector
    Definition Classes
    LightGBMClassificationModel → ProbabilisticClassificationModel
  103. def predictRaw(features: Vector): Vector
    Definition Classes
    LightGBMClassificationModel → ClassificationModel
  104. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  105. def probability2prediction(probability: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  106. final val probabilityCol: Param[String]
    Definition Classes
    HasProbabilityCol
  107. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  108. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  109. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  110. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  111. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  112. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  113. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  114. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    LightGBMClassificationModel → PythonWrappable
  115. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  116. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  117. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  118. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  119. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  120. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  121. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  122. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  123. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  124. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  125. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  126. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  127. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  128. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  129. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  130. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  131. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  132. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  133. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  134. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  135. def raw2prediction(rawPrediction: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel
  136. def raw2probability(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  137. def raw2probabilityInPlace(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    LightGBMClassificationModel → ProbabilisticClassificationModel
  138. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  139. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  140. def saveNativeModel(filename: String, overwrite: Boolean): Unit
  141. final def set(paramPair: ParamPair[_]): LightGBMClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  142. final def set(param: String, value: Any): LightGBMClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  143. final def set[T](param: Param[T], value: T): LightGBMClassificationModel.this.type
    Definition Classes
    Params
  144. def setActualNumClasses(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    HasActualNumClasses
  145. final def setDefault(paramPairs: ParamPair[_]*): LightGBMClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  146. final def setDefault[T](param: Param[T], value: T): LightGBMClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  147. def setFeaturesCol(value: String): LightGBMClassificationModel
    Definition Classes
    PredictionModel
  148. def setFeaturesShapCol(value: String): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  149. def setLeafPredictionCol(value: String): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  150. def setLightGBMBooster(value: LightGBMBooster): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  151. def setNumIterations(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  152. def setParent(parent: Estimator[LightGBMClassificationModel]): LightGBMClassificationModel
    Definition Classes
    Model
  153. def setPredictionCol(value: String): LightGBMClassificationModel
    Definition Classes
    PredictionModel
  154. def setProbabilityCol(value: String): LightGBMClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  155. def setRawPredictionCol(value: String): LightGBMClassificationModel
    Definition Classes
    ClassificationModel
  156. def setStartIteration(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  157. def setThresholds(value: Array[Double]): LightGBMClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  158. val startIteration: IntParam
    Definition Classes
    LightGBMModelParams
  159. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  160. val thresholds: DoubleArrayParam
    Definition Classes
    HasThresholds
  161. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  162. def transform(dataset: Dataset[_]): DataFrame

    Implementation based on ProbabilisticClassifier with slight modifications to avoid calling raw2probabilityInPlace to defer the probability calculation to lightgbm native code.

    Implementation based on ProbabilisticClassifier with slight modifications to avoid calling raw2probabilityInPlace to defer the probability calculation to lightgbm native code.

    dataset

    input dataset

    returns

    transformed dataset

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

Inherited from BasicLogging

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from HasActualNumClasses

Inherited from LightGBMPredictionParams

Inherited from LightGBMModelMethods

Inherited from LightGBMModelParams

Inherited from Wrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from ProbabilisticClassificationModel[Vector, LightGBMClassificationModel]

Inherited from ProbabilisticClassifierParams

Inherited from HasThresholds

Inherited from HasProbabilityCol

Inherited from ClassificationModel[Vector, LightGBMClassificationModel]

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from PredictionModel[Vector, LightGBMClassificationModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[LightGBMClassificationModel]

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