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

Model produced by LightGBMClassifier.

Linear Supertypes
SynapseMLLogging, ComplexParamsWritable, MLWritable, HasActualNumClasses, LightGBMPredictionParams, LightGBMModelMethods, LightGBMModelParams, Wrappable, DotnetWrappable, 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. SynapseMLLogging
  3. ComplexParamsWritable
  4. MLWritable
  5. HasActualNumClasses
  6. LightGBMPredictionParams
  7. LightGBMModelMethods
  8. LightGBMModelParams
  9. Wrappable
  10. DotnetWrappable
  11. RWrappable
  12. PythonWrappable
  13. BaseWrappable
  14. ProbabilisticClassificationModel
  15. ProbabilisticClassifierParams
  16. HasThresholds
  17. HasProbabilityCol
  18. ClassificationModel
  19. ClassifierParams
  20. HasRawPredictionCol
  21. PredictionModel
  22. PredictorParams
  23. HasPredictionCol
  24. HasFeaturesCol
  25. HasLabelCol
  26. Model
  27. Transformer
  28. PipelineStage
  29. Logging
  30. Params
  31. Serializable
  32. Serializable
  33. Identifiable
  34. AnyRef
  35. 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. def dotnetAdditionalMethods: String
    Definition Classes
    DotnetWrappable
  16. def dotnetClass(): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  17. lazy val dotnetClassName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  18. lazy val dotnetClassNameString: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  19. lazy val dotnetClassWrapperName: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  20. lazy val dotnetCopyrightLines: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  21. def dotnetExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  22. def dotnetExtraMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  23. lazy val dotnetInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  24. def dotnetMLReadWriteMethods: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  25. lazy val dotnetNamespace: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  26. lazy val dotnetObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  27. def dotnetParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  28. def dotnetParamGetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  29. def dotnetParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  30. def dotnetParamSetters: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  31. def dotnetWrapAsTypeMethod: String
    Attributes
    protected
    Definition Classes
    DotnetWrappable
  32. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  33. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  34. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  35. def explainParams(): String
    Definition Classes
    Params
  36. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  37. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  38. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  39. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  40. 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
  41. val featuresShapCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  42. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  43. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  44. def getActualNumClasses: Int
    Definition Classes
    HasActualNumClasses
  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. final def getProbabilityCol: String
    Definition Classes
    HasProbabilityCol
  70. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  71. 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
  72. def getStartIteration: Int
    Definition Classes
    LightGBMModelParams
  73. def getThresholds: Array[Double]
    Definition Classes
    HasThresholds
  74. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  75. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  76. def hasParent: Boolean
    Definition Classes
    Model
  77. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  78. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  79. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  81. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  82. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  83. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  84. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  85. val leafPredictionCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  86. val lightGBMBooster: LightGBMBoosterParam
    Definition Classes
    LightGBMModelParams
  87. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  88. def logBase(info: Map[String, String], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  89. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  90. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  91. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  92. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  93. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  94. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  95. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  96. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  97. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  98. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  99. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  100. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  101. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  102. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  103. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  104. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  105. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  106. def makeDotnetFile(conf: CodegenConfig): Unit
    Definition Classes
    DotnetWrappable
  107. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  108. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  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. def numClasses: Int
    Definition Classes
    LightGBMClassificationModel → ClassificationModel
  113. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  114. val numIterations: IntParam
    Definition Classes
    LightGBMModelParams
  115. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  116. var parent: Estimator[LightGBMClassificationModel]
    Definition Classes
    Model
  117. def predict(features: Vector): Double
    Definition Classes
    ClassificationModel → PredictionModel
  118. def predictColumn: Column
    Attributes
    protected
  119. val predictDisableShapeCheck: BooleanParam
    Definition Classes
    LightGBMPredictionParams
  120. 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
  121. def predictProbability(features: Vector): Vector
    Definition Classes
    LightGBMClassificationModel → ProbabilisticClassificationModel
  122. def predictRaw(features: Vector): Vector
    Definition Classes
    LightGBMClassificationModel → ClassificationModel
  123. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  124. def probability2prediction(probability: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  125. final val probabilityCol: Param[String]
    Definition Classes
    HasProbabilityCol
  126. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  127. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  128. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  129. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  130. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  131. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  132. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  133. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    LightGBMClassificationModel → PythonWrappable
  134. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  135. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  136. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  137. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  138. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  139. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  140. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  141. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  142. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  143. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  144. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  145. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  146. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  147. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  148. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  149. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  150. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  151. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  152. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  153. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  154. def raw2prediction(rawPrediction: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel
  155. def raw2probability(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  156. def raw2probabilityInPlace(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    LightGBMClassificationModel → ProbabilisticClassificationModel
  157. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  158. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  159. 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
  160. final def set(paramPair: ParamPair[_]): LightGBMClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  161. final def set(param: String, value: Any): LightGBMClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  162. final def set[T](param: Param[T], value: T): LightGBMClassificationModel.this.type
    Definition Classes
    Params
  163. def setActualNumClasses(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    HasActualNumClasses
  164. final def setDefault(paramPairs: ParamPair[_]*): LightGBMClassificationModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  165. final def setDefault[T](param: Param[T], value: T): LightGBMClassificationModel.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  166. def setFeaturesCol(value: String): LightGBMClassificationModel
    Definition Classes
    PredictionModel
  167. def setFeaturesShapCol(value: String): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  168. def setLeafPredictionCol(value: String): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  169. def setLightGBMBooster(value: LightGBMBooster): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  170. def setNumIterations(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  171. def setParent(parent: Estimator[LightGBMClassificationModel]): LightGBMClassificationModel
    Definition Classes
    Model
  172. def setPredictDisableShapeCheck(value: Boolean): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  173. def setPredictionCol(value: String): LightGBMClassificationModel
    Definition Classes
    PredictionModel
  174. def setProbabilityCol(value: String): LightGBMClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  175. def setRawPredictionCol(value: String): LightGBMClassificationModel
    Definition Classes
    ClassificationModel
  176. def setStartIteration(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  177. def setThresholds(value: Array[Double]): LightGBMClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  178. val startIteration: IntParam
    Definition Classes
    LightGBMModelParams
  179. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  180. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  181. val thresholds: DoubleArrayParam
    Definition Classes
    HasThresholds
  182. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  183. 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
  184. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  185. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  186. final def transformImpl(dataset: Dataset[_]): DataFrame
    Definition Classes
    ClassificationModel → PredictionModel
  187. def transformSchema(schema: StructType): StructType
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel → PredictionModel → PipelineStage
  188. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  189. val uid: String
    Definition Classes
    LightGBMClassificationModel → SynapseMLLogging → Identifiable
  190. def updateBoosterParamsBeforePredict(): Unit
    Attributes
    protected
    Definition Classes
    LightGBMModelMethods
  191. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ProbabilisticClassifierParams → ClassifierParams → PredictorParams
  192. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  193. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  194. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  195. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from HasActualNumClasses

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 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