org.apache.spark.ml.mleap.classification

SVM

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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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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Instance Constructors

  1. new SVM()

  2. new SVM(uid: String)

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

  4. final def $[T](param: Param[T]): T

    Attributes
    protected
    Definition Classes
    Params

  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  6. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. final def clear(param: Param[_]): SVM.this.type

    Definition Classes
    Params

  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  10. def copy(extra: ParamMap): SVM

    Definition Classes
    SVM → Predictor → Estimator → PipelineStage → Params

  11. def copyValues[T <: Params](to: T, extra: ParamMap): T

    Attributes
    protected
    Definition Classes
    Params

  12. final def defaultCopy[T <: Params](extra: ParamMap): T

    Attributes
    protected
    Definition Classes
    Params

  13. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  15. def explainParam(param: Param[_]): String

    Definition Classes
    Params

  16. def explainParams(): String

    Definition Classes
    Params

  17. def extractLabeledPoints(dataset: DataFrame): RDD[LabeledPoint]

    Attributes
    protected
    Definition Classes
    Predictor

  18. final def extractParamMap(): ParamMap

    Definition Classes
    Params

  19. final def extractParamMap(extra: ParamMap): ParamMap

    Definition Classes
    Params

  20. final val featuresCol: Param[String]

    Definition Classes
    HasFeaturesCol

  21. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  22. def fit(dataset: DataFrame): SVMModel

    Definition Classes
    Predictor → Estimator

  23. def fit(dataset: DataFrame, paramMaps: Array[ParamMap]): Seq[SVMModel]

    Definition Classes
    Estimator

  24. def fit(dataset: DataFrame, paramMap: ParamMap): SVMModel

    Definition Classes
    Estimator

  25. def fit(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SVMModel

    Definition Classes
    Estimator
    Annotations
    @varargs()

  26. final val fitIntercept: BooleanParam

    Param for whether to fit the intercept.

    Param for whether to fit the intercept.

    Definition Classes
    SVMBase

  27. final def get[T](param: Param[T]): Option[T]

    Definition Classes
    Params

  28. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

  29. final def getDefault[T](param: Param[T]): Option[T]

    Definition Classes
    Params

  30. final def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol

  31. final def getFitIntercept: Boolean

    Definition Classes
    SVMBase

  32. final def getLabelCol: String

    Definition Classes
    HasLabelCol

  33. final def getMiniBatchFraction: Double

    Definition Classes
    SVMBase

  34. final def getNumIterations: Int

    Definition Classes
    SVMBase

  35. final def getOrDefault[T](param: Param[T]): T

    Definition Classes
    Params

  36. def getParam(paramName: String): Param[Any]

    Definition Classes
    Params

  37. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol

  38. final def getProbabilityCol: String

    Definition Classes
    HasProbabilityCol

  39. final def getRawPredictionCol: String

    Definition Classes
    HasRawPredictionCol

  40. final def getRegParam: Double

    Definition Classes
    SVMBase

  41. final def getStepSize: Double

    Definition Classes
    SVMBase

  42. final def getThreshold: Option[Double]

    Definition Classes
    SVMBase

  43. def getThresholds: Array[Double]

    Definition Classes
    HasThresholds

  44. final def hasDefault[T](param: Param[T]): Boolean

    Definition Classes
    Params

  45. def hasParam(paramName: String): Boolean

    Definition Classes
    Params

  46. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  47. final def isDefined(param: Param[_]): Boolean

    Definition Classes
    Params

  48. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  49. final def isSet(param: Param[_]): Boolean

    Definition Classes
    Params

  50. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  51. final val labelCol: Param[String]

    Definition Classes
    HasLabelCol

  52. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

  53. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  54. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  55. def logError(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  56. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  57. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  58. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  59. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

  60. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  61. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  62. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  63. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  64. final val miniBatchFraction: DoubleParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase

  65. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  66. final def notify(): Unit

    Definition Classes
    AnyRef

  67. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  68. final val numIterations: IntParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase

  69. lazy val params: Array[Param[_]]

    Definition Classes
    Params

  70. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol

  71. final val probabilityCol: Param[String]

    Definition Classes
    HasProbabilityCol

  72. final val rawPredictionCol: Param[String]

    Definition Classes
    HasRawPredictionCol

  73. final val regParam: DoubleParam

    Param for number of iterations.

    Param for number of iterations.

    Definition Classes
    SVMBase

  74. final def set(paramPair: ParamPair[_]): SVM.this.type

    Attributes
    protected
    Definition Classes
    Params

  75. final def set(param: String, value: Any): SVM.this.type

    Attributes
    protected
    Definition Classes
    Params

  76. final def set[T](param: Param[T], value: T): SVM.this.type

    Definition Classes
    Params

  77. final def setDefault(paramPairs: ParamPair[_]*): SVM.this.type

    Attributes
    protected
    Definition Classes
    Params

  78. final def setDefault[T](param: Param[T], value: T): SVM.this.type

    Attributes
    protected
    Definition Classes
    Params

  79. def setFeaturesCol(value: String): SVM

    Definition Classes
    Predictor

  80. def setFitIntercept(value: Boolean): SVM.this.type

  81. def setLabelCol(value: String): SVM

    Definition Classes
    Predictor

  82. def setMiniBatchFraction(value: Double): SVM.this.type

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

  84. def setPredictionCol(value: String): SVM

    Definition Classes
    Predictor

  85. def setProbabilityCol(value: String): SVM

    Definition Classes
    ProbabilisticClassifier

  86. def setRawPredictionCol(value: String): SVM

    Definition Classes
    Classifier

  87. def setRegParam(value: Double): SVM.this.type

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

  89. def setThreshold(value: Option[Double]): SVM.this.type

  90. def setThresholds(value: Array[Double]): SVM

    Definition Classes
    ProbabilisticClassifier

  91. final val stepSize: DoubleParam

    Param for step size.

    Param for step size.

    Definition Classes
    SVMBase

  92. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef

  93. final val threshold: Param[Option[Double]]

    Param for threshold.

    Param for threshold.

    Definition Classes
    SVMBase

  94. final val thresholds: DoubleArrayParam

    Definition Classes
    HasThresholds

  95. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any

  96. def train(dataset: DataFrame): SVMModel

    Attributes
    protected
    Definition Classes
    SVM → Predictor

  97. def transformSchema(schema: StructType): StructType

    Definition Classes
    Predictor → PipelineStage

  98. def transformSchema(schema: StructType, logging: Boolean): StructType

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  99. val uid: String

    Definition Classes
    SVM → Identifiable

  100. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

    Attributes
    protected
    Definition Classes
    ProbabilisticClassifierParams → ClassifierParams → PredictorParams

  101. def validateParams(): Unit

    Definition Classes
    Params

  102. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  103. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  104. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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