Packages

class SVM extends ProbabilisticClassifier[Vector, SVM, SVMModel] with SVMBase

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

Instance Constructors

  1. new SVM()
  2. new SVM(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. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. final def clear(param: Param[_]): SVM.this.type
    Definition Classes
    Params
  7. def clearThreshold(): SVM.this.type
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  9. def copy(extra: ParamMap): SVM
    Definition Classes
    SVM → Predictor → Estimator → 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. def extractInstances(dataset: Dataset[_], numClasses: Int): RDD[Instance]
    Attributes
    protected
    Definition Classes
    ClassifierParams
  17. def extractInstances(dataset: Dataset[_], validateInstance: (Instance) ⇒ Unit): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  18. def extractInstances(dataset: Dataset[_]): RDD[Instance]
    Attributes
    protected
    Definition Classes
    PredictorParams
  19. def extractLabeledPoints(dataset: Dataset[_], numClasses: Int): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Classifier
  20. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]
    Attributes
    protected
    Definition Classes
    Predictor
  21. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  22. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  23. final val featuresCol: Param[String]
    Definition Classes
    HasFeaturesCol
  24. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  25. def fit(dataset: Dataset[_]): SVMModel
    Definition Classes
    Predictor → Estimator
  26. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[SVMModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  27. def fit(dataset: Dataset[_], paramMap: ParamMap): SVMModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  28. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SVMModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  29. final val fitIntercept: BooleanParam

    Param for whether to fit the intercept.

    Param for whether to fit the intercept.

    Definition Classes
    SVMBase
  30. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  31. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  32. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  33. final def getFeaturesCol: String
    Definition Classes
    HasFeaturesCol
  34. final def getFitIntercept: Boolean

    Definition Classes
    SVMBase
  35. final def getLabelCol: String
    Definition Classes
    HasLabelCol
  36. final def getMiniBatchFraction: Double

    Definition Classes
    SVMBase
  37. def getNumClasses(dataset: Dataset[_], maxNumClasses: Int): Int
    Attributes
    protected
    Definition Classes
    Classifier
  38. final def getNumIterations: Int

    Definition Classes
    SVMBase
  39. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  40. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  41. final def getPredictionCol: String
    Definition Classes
    HasPredictionCol
  42. final def getProbabilityCol: String
    Definition Classes
    HasProbabilityCol
  43. final def getRawPredictionCol: String
    Definition Classes
    HasRawPredictionCol
  44. final def getRegParam: Double

    Definition Classes
    SVMBase
  45. final def getStepSize: Double

    Definition Classes
    SVMBase
  46. final def getThreshold: Double

    Definition Classes
    SVMBase
  47. def getThresholds: Array[Double]
    Definition Classes
    HasThresholds
  48. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  49. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  50. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  51. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  52. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  53. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  54. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  55. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  56. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  57. final val labelCol: Param[String]
    Definition Classes
    HasLabelCol
  58. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  59. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  63. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  66. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. final val miniBatchFraction: DoubleParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  71. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  72. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  73. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  74. final val numIterations: IntParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  75. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  76. final val predictionCol: Param[String]
    Definition Classes
    HasPredictionCol
  77. final val probabilityCol: Param[String]
    Definition Classes
    HasProbabilityCol
  78. final val rawPredictionCol: Param[String]
    Definition Classes
    HasRawPredictionCol
  79. final val regParam: DoubleParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase
  80. final def set(paramPair: ParamPair[_]): SVM.this.type
    Attributes
    protected
    Definition Classes
    Params
  81. final def set(param: String, value: Any): SVM.this.type
    Attributes
    protected
    Definition Classes
    Params
  82. final def set[T](param: Param[T], value: T): SVM.this.type
    Definition Classes
    Params
  83. final def setDefault(paramPairs: ParamPair[_]*): SVM.this.type
    Attributes
    protected
    Definition Classes
    Params
  84. final def setDefault[T](param: Param[T], value: T): SVM.this.type
    Attributes
    protected
    Definition Classes
    Params
  85. def setFeaturesCol(value: String): SVM
    Definition Classes
    Predictor
  86. def setFitIntercept(value: Boolean): SVM.this.type

  87. def setLabelCol(value: String): SVM
    Definition Classes
    Predictor
  88. def setMiniBatchFraction(value: Double): SVM.this.type

  89. def setNumIterations(value: Int): SVM.this.type

  90. def setPredictionCol(value: String): SVM
    Definition Classes
    Predictor
  91. def setProbabilityCol(value: String): SVM
    Definition Classes
    ProbabilisticClassifier
  92. def setRawPredictionCol(value: String): SVM
    Definition Classes
    Classifier
  93. def setRegParam(value: Double): SVM.this.type

  94. def setStepSize(value: Double): SVM.this.type

  95. def setThreshold(value: Double): SVM.this.type

  96. def setThresholds(value: Array[Double]): SVM
    Definition Classes
    ProbabilisticClassifier
  97. final val stepSize: DoubleParam

    Param for step size.

    Param for step size.

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

    Param for threshold.

    Param for threshold.

    Definition Classes
    SVMBase
  100. val thresholds: DoubleArrayParam
    Definition Classes
    HasThresholds
  101. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  102. def train(dataset: Dataset[_]): SVMModel
    Attributes
    protected
    Definition Classes
    SVM → Predictor
  103. def transformSchema(schema: StructType): StructType
    Definition Classes
    Predictor → PipelineStage
  104. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  105. val uid: String
    Definition Classes
    SVM → Identifiable
  106. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType
    Attributes
    protected
    Definition Classes
    ProbabilisticClassifierParams → ClassifierParams → PredictorParams
  107. def validateLabel(label: Double, numClasses: Int): Unit
    Attributes
    protected
    Definition Classes
    Classifier
  108. def validateNumClasses(numClasses: Int): Unit
    Attributes
    protected
    Definition Classes
    Classifier
  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
    @throws( ... ) @native()

Inherited from SVMBase

Inherited from ProbabilisticClassifier[Vector, SVM, SVMModel]

Inherited from ProbabilisticClassifierParams

Inherited from HasThresholds

Inherited from HasProbabilityCol

Inherited from Classifier[Vector, SVM, SVMModel]

Inherited from ClassifierParams

Inherited from HasRawPredictionCol

Inherited from Predictor[Vector, SVM, SVMModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[SVMModel]

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

setParam

Ungrouped