Packages

class SVMModel extends ProbabilisticClassificationModel[Vector, SVMModel] with SVMBase

Linear Supertypes
SVMBase, ProbabilisticClassificationModel[Vector, SVMModel], ProbabilisticClassifierParams, HasThresholds, HasProbabilityCol, ClassificationModel[Vector, SVMModel], ClassifierParams, HasRawPredictionCol, PredictionModel[Vector, SVMModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[SVMModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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  2. By Inheritance
Inherited
  1. SVMModel
  2. SVMBase
  3. ProbabilisticClassificationModel
  4. ProbabilisticClassifierParams
  5. HasThresholds
  6. HasProbabilityCol
  7. ClassificationModel
  8. ClassifierParams
  9. HasRawPredictionCol
  10. PredictionModel
  11. PredictorParams
  12. HasPredictionCol
  13. HasFeaturesCol
  14. HasLabelCol
  15. Model
  16. Transformer
  17. PipelineStage
  18. Logging
  19. Params
  20. Serializable
  21. Serializable
  22. Identifiable
  23. AnyRef
  24. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new SVMModel(model: mllib.classification.SVMModel)
  2. new SVMModel(uid: String, model: mllib.classification.SVMModel)

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. final def clear(param: Param[_]): SVMModel.this.type
    Definition Classes
    Params
  7. def clearThreshold(): SVMModel.this.type
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native() @HotSpotIntrinsicCandidate()
  9. def copy(extra: ParamMap): SVMModel
    Definition Classes
    SVMModel → Model → Transformer → PipelineStage → Params
  10. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  11. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  12. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  14. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  15. def explainParams(): String
    Definition Classes
    Params
  16. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  17. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  18. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  19. def featuresDataType: DataType
    Attributes
    protected
    Definition Classes
    PredictionModel
  20. final val fitIntercept: BooleanParam

    Param for whether to fit the intercept.

    Param for whether to fit the intercept.

    Definition Classes
    SVMBase
  21. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  22. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  23. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  24. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  25. final def getFitIntercept: Boolean

    Definition Classes
    SVMBase
  26. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  27. final def getMiniBatchFraction: Double

    Definition Classes
    SVMBase
  28. final def getNumIterations: Int

    Definition Classes
    SVMBase
  29. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  30. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  31. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  32. final def getProbabilityCol: String
    Definition Classes
    HasProbabilityCol
  33. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  34. final def getRegParam: Double

    Definition Classes
    SVMBase
  35. final def getStepSize: Double

    Definition Classes
    SVMBase
  36. final def getThreshold: Double

    Definition Classes
    SVMBase
  37. def getThresholds: Array[Double]
    Definition Classes
    HasThresholds
  38. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  39. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  40. def hasParent: Boolean
    Definition Classes
    Model
  41. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  42. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  43. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  44. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  45. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  46. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  47. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  48. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  49. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  50. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  51. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  52. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  57. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def margin(features: Vector): Double
  62. final val miniBatchFraction: DoubleParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  63. val model: mllib.classification.SVMModel
  64. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  65. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  66. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  67. def numClasses: Int
    Definition Classes
    SVMModel → ClassificationModel
  68. def numFeatures: Int
    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  69. final val numIterations: IntParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  70. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  71. var parent: Estimator[SVMModel]
    Definition Classes
    Model
  72. def predict(features: Vector): Double
    Definition Classes
    SVMModel → ClassificationModel → PredictionModel
  73. def predictProbability(features: Vector): Vector
    Definition Classes
    ProbabilisticClassificationModel
    Annotations
    @Since( "3.0.0" )
  74. def predictRaw(features: Vector): Vector
    Definition Classes
    SVMModel → ClassificationModel
  75. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  76. def probability2prediction(probability: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  77. final val probabilityCol: Param[String]
    Definition Classes
    HasProbabilityCol
  78. def raw2prediction(rawPrediction: Vector): Double
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel
  79. def raw2probability(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    ProbabilisticClassificationModel
  80. def raw2probabilityInPlace(rawPrediction: Vector): Vector
    Attributes
    protected
    Definition Classes
    SVMModel → ProbabilisticClassificationModel
  81. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  82. final val regParam: DoubleParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  83. final def set(paramPair: ParamPair[_]): SVMModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  84. final def set(param: String, value: Any): SVMModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  85. final def set[T](param: Param[T], value: T): SVMModel.this.type
    Definition Classes
    Params
  86. final def setDefault(paramPairs: ParamPair[_]*): SVMModel.this.type
    Attributes
    protected
    Definition Classes
    Params
  87. final def setDefault[T](param: Param[T], value: T): SVMModel.this.type
    Attributes
    protected[ml]
    Definition Classes
    Params
  88. def setFeaturesCol(value: String): SVMModel
    Definition Classes
    PredictionModel
  89. def setParent(parent: Estimator[SVMModel]): SVMModel
    Definition Classes
    Model
  90. def setPredictionCol(value: String): SVMModel
    Definition Classes
    PredictionModel
  91. def setProbabilityCol(value: String): SVMModel
    Definition Classes
    ProbabilisticClassificationModel
  92. def setRawPredictionCol(value: String): SVMModel
    Definition Classes
    ClassificationModel
  93. def setThreshold(value: Double): SVMModel.this.type
  94. def setThresholds(value: Array[Double]): SVMModel
    Definition Classes
    ProbabilisticClassificationModel
  95. final val stepSize: DoubleParam

    Param for step size.

    Param for step size.

    Definition Classes
    SVMBase
  96. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  97. final val threshold: DoubleParam

    Param for threshold.

    Param for threshold.

    Definition Classes
    SVMBase
  98. val thresholds: DoubleArrayParam
    Definition Classes
    HasThresholds
  99. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  100. def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel → PredictionModel → Transformer
  101. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  102. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  103. final def transformImpl(dataset: Dataset[_]): DataFrame
    Definition Classes
    ClassificationModel → PredictionModel
  104. def transformSchema(schema: StructType): StructType
    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel → PredictionModel → PipelineStage
  105. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  106. val uid: String
    Definition Classes
    SVMModel → Identifiable
  107. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ProbabilisticClassifierParams → ClassifierParams → PredictorParams
  108. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  109. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  110. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] ) @Deprecated
    Deprecated

Inherited from SVMBase

Inherited from ProbabilisticClassificationModel[Vector, SVMModel]

Inherited from ProbabilisticClassifierParams

Inherited from HasThresholds

Inherited from HasProbabilityCol

Inherited from ClassificationModel[Vector, SVMModel]

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from PredictionModel[Vector, SVMModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[SVMModel]

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

getParam

param

Ungrouped