ml.combust.mleap.core.classification

SupportVectorMachineModel

case class SupportVectorMachineModel(coefficients: Vector, intercept: Double, thresholds: Option[Array[Double]] = ...) extends ProbabilisticClassificationModel with Serializable with Product

Class for support vector machine models.

coefficients

coefficients of SVM

intercept

intercept for SVM

thresholds

threshold for pegging prediction

Linear Supertypes
Product, Equals, Serializable, Serializable, ProbabilisticClassificationModel, ClassificationModel, Model, AnyRef, Any
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  1. SupportVectorMachineModel
  2. Product
  3. Equals
  4. Serializable
  5. Serializable
  6. ProbabilisticClassificationModel
  7. ClassificationModel
  8. Model
  9. AnyRef
  10. Any
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Instance Constructors

  1. new SupportVectorMachineModel(coefficients: Vector, intercept: Double, thresholds: Option[Array[Double]] = ...)

    coefficients

    coefficients of SVM

    intercept

    intercept for SVM

    thresholds

    threshold for pegging prediction

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 ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  6. def apply(features: Vector): Double

    Alias for ml.combust.mleap.core.classification.ClassificationModel#predict.

    Alias for ml.combust.mleap.core.classification.ClassificationModel#predict.

    features

    feature vector

    returns

    prediction

    Definition Classes
    ClassificationModel

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def clone(): AnyRef

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

  9. val coefficients: Vector

    coefficients of SVM

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

    Definition Classes
    AnyRef

  11. def finalize(): Unit

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

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

    Definition Classes
    AnyRef → Any

  13. def inputSchema: StructType

    Definition Classes
    ProbabilisticClassificationModel → Model

  14. val intercept: Double

    intercept for SVM

  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  17. final def notify(): Unit

    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  19. val numClasses: Int

    Number of classes this model predicts.

    Number of classes this model predicts.

    2 indicates this is a binary classification model. Greater than 2 indicates a multinomial classifier.

    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

  20. val numFeatures: Int

    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

  21. def outputSchema: StructType

    Definition Classes
    ProbabilisticClassificationModel → Model

  22. def predict(features: Vector): Double

    Predict class based on feature vector.

    Predict class based on feature vector.

    features

    feature vector

    returns

    predicted class or probability

    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel

  23. def predictProbabilities(features: Vector): Vector

    Definition Classes
    ProbabilisticClassificationModel

  24. def predictRaw(features: Vector): Vector

    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

  25. def predictWithProbability(features: Vector): (Double, Double)

    Definition Classes
    ProbabilisticClassificationModel

  26. def probabilityToPrediction(probability: Vector): Double

    Definition Classes
    ProbabilisticClassificationModel

  27. def probabilityToPredictionIndex(probability: Vector): Int

    Definition Classes
    ProbabilisticClassificationModel

  28. def rawToPrediction(raw: Vector): Double

    Definition Classes
    ProbabilisticClassificationModel

  29. def rawToProbability(raw: Vector): Vector

    Definition Classes
    ProbabilisticClassificationModel

  30. def rawToProbabilityInPlace(raw: Vector): Vector

    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

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

    Definition Classes
    AnyRef

  32. val thresholds: Option[Array[Double]]

    threshold for pegging prediction

    threshold for pegging prediction

    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

  33. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Product

Inherited from Equals

Inherited from Serializable

Inherited from Serializable

Inherited from ProbabilisticClassificationModel

Inherited from ClassificationModel

Inherited from Model

Inherited from AnyRef

Inherited from Any

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