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[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  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. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. final val fitIntercept: BooleanParam

    Param for whether to fit the intercept.

    Param for whether to fit the intercept.

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

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

    Definition Classes
    SVMBase
  29. final def getNumIterations: Int

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

    Definition Classes
    SVMBase
  36. final def getStepSize: Double

    Definition Classes
    SVMBase
  37. final def getThreshold: Double

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

    Param for number of iterations.

    Param for number of iterations.

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

    Param for number of iterations.

    Param for number of iterations.

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

    Param for number of iterations.

    Param for number of iterations.

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

    Param for step size.

    Param for step size.

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

    Param for threshold.

    Param for threshold.

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

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