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, 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. 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. val actualNumClasses: IntParam
    Definition Classes
    HasActualNumClasses
  2. final def clear(param: Param[_]): LightGBMClassificationModel.this.type
    Definition Classes
    Params
  3. def copy(extra: ParamMap): LightGBMClassificationModel
    Definition Classes
    LightGBMClassificationModel → Model → Transformer → PipelineStage → Params
  4. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  5. def explainParams(): String
    Definition Classes
    Params
  6. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  7. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  8. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  9. val featuresShapCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  10. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  11. def getActualNumClasses: Int
    Definition Classes
    HasActualNumClasses
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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
  17. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  18. 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
  19. 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
  20. 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
  21. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  22. def getFeaturesShapCol: String
    Definition Classes
    LightGBMPredictionParams
  23. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  24. def getLeafPredictionCol: String
    Definition Classes
    LightGBMPredictionParams
  25. def getLightGBMBooster: LightGBMBooster
    Definition Classes
    LightGBMModelParams
  26. def getModel: LightGBMBooster

    Alias for same method

    Alias for same method

    returns

    The LightGBM Booster.

    Definition Classes
    LightGBMModelParams
  27. def getNativeModel(): String

    Gets the native model serialized representation as a string.

    Gets the native model serialized representation as a string.

    Definition Classes
    LightGBMModelMethods
  28. def getNumIterations: Int
    Definition Classes
    LightGBMModelParams
  29. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  30. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  31. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  32. def getPredictDisableShapeCheck: Boolean
    Definition Classes
    LightGBMPredictionParams
  33. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  34. final def getProbabilityCol: String
    Definition Classes
    HasProbabilityCol
  35. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  36. 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
  37. def getStartIteration: Int
    Definition Classes
    LightGBMModelParams
  38. def getThresholds: Array[Double]
    Definition Classes
    HasThresholds
  39. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  40. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  41. def hasParent: Boolean
    Definition Classes
    Model
  42. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  43. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  44. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  45. val leafPredictionCol: Param[String]
    Definition Classes
    LightGBMPredictionParams
  46. val lightGBMBooster: LightGBMBoosterParam
    Definition Classes
    LightGBMModelParams
  47. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  48. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  49. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  50. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  51. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  52. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  53. def numClasses: Int
    Definition Classes
    LightGBMClassificationModel → ClassificationModel
  54. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  55. val numIterations: IntParam
    Definition Classes
    LightGBMModelParams
  56. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  57. var parent: Estimator[LightGBMClassificationModel]
    Definition Classes
    Model
  58. def predict(features: Vector): Double
    Definition Classes
    ClassificationModel → PredictionModel
  59. val predictDisableShapeCheck: BooleanParam
    Definition Classes
    LightGBMPredictionParams
  60. def predictProbability(features: Vector): Vector
    Definition Classes
    LightGBMClassificationModel → ProbabilisticClassificationModel
  61. def predictRaw(features: Vector): Vector
    Definition Classes
    LightGBMClassificationModel → ClassificationModel
  62. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  63. final val probabilityCol: Param[String]
    Definition Classes
    HasProbabilityCol
  64. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  65. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  66. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  67. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  68. 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
  69. final def set[T](param: Param[T], value: T): LightGBMClassificationModel.this.type
    Definition Classes
    Params
  70. def setActualNumClasses(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    HasActualNumClasses
  71. def setFeaturesCol(value: String): LightGBMClassificationModel
    Definition Classes
    PredictionModel
  72. def setFeaturesShapCol(value: String): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  73. def setLeafPredictionCol(value: String): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  74. def setLightGBMBooster(value: LightGBMBooster): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  75. def setNumIterations(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  76. def setParent(parent: Estimator[LightGBMClassificationModel]): LightGBMClassificationModel
    Definition Classes
    Model
  77. def setPredictDisableShapeCheck(value: Boolean): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMPredictionParams
  78. def setPredictionCol(value: String): LightGBMClassificationModel
    Definition Classes
    PredictionModel
  79. def setProbabilityCol(value: String): LightGBMClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  80. def setRawPredictionCol(value: String): LightGBMClassificationModel
    Definition Classes
    ClassificationModel
  81. def setStartIteration(value: Int): LightGBMClassificationModel.this.type
    Definition Classes
    LightGBMModelParams
  82. def setThresholds(value: Array[Double]): LightGBMClassificationModel
    Definition Classes
    ProbabilisticClassificationModel
  83. val startIteration: IntParam
    Definition Classes
    LightGBMModelParams
  84. val thresholds: DoubleArrayParam
    Definition Classes
    HasThresholds
  85. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  86. 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
  87. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  88. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  89. final def transformImpl(dataset: Dataset[_]): DataFrame
    Definition Classes
    ClassificationModel → PredictionModel
  90. def transformSchema(schema: StructType): StructType
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel → PredictionModel → PipelineStage
  91. val uid: String
    Definition Classes
    LightGBMClassificationModel → SynapseMLLogging → Identifiable
  92. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable