Class/Object

ml.combust.mleap.core.classification

SupportVectorMachineModel

Related Docs: object SupportVectorMachineModel | package classification

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

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

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    coefficients

    coefficients of SVM

    intercept

    intercept for SVM

    thresholds

    threshold for pegging prediction

Value Members

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

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    AnyRef → Any

  4. def apply(features: Vector): Double

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    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

  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. def clone(): AnyRef

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

  7. val coefficients: Vector

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    coefficients of SVM

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

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    Definition Classes
    AnyRef

  9. def finalize(): Unit

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

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

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    Definition Classes
    AnyRef → Any

  11. def inputSchema: StructType

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    Definition Classes
    ProbabilisticClassificationModel → Model

  12. val intercept: Double

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    intercept for SVM

  13. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    AnyRef

  15. final def notify(): Unit

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    Definition Classes
    AnyRef

  16. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  17. val numClasses: Int

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    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

  18. val numFeatures: Int

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    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

  19. def outputSchema: StructType

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    Definition Classes
    ProbabilisticClassificationModel → Model

  20. def predict(features: Vector): Double

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    Predict class based on feature vector.

    Predict class based on feature vector.

    features

    feature vector

    returns

    predicted class or probability

    Definition Classes
    ProbabilisticClassificationModel → ClassificationModel

  21. def predictProbabilities(features: Vector): Vector

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    Definition Classes
    ProbabilisticClassificationModel

  22. def predictRaw(features: Vector): Vector

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    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

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

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    Definition Classes
    ProbabilisticClassificationModel

  24. def probabilityToPrediction(probability: Vector): Double

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    Definition Classes
    ProbabilisticClassificationModel

  25. def probabilityToPredictionIndex(probability: Vector): Int

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    Definition Classes
    ProbabilisticClassificationModel

  26. def rawToPrediction(raw: Vector): Double

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    Definition Classes
    ProbabilisticClassificationModel

  27. def rawToProbability(raw: Vector): Vector

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    Definition Classes
    ProbabilisticClassificationModel

  28. def rawToProbabilityInPlace(raw: Vector): Vector

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    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

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

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    Definition Classes
    AnyRef

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

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    threshold for pegging prediction

    threshold for pegging prediction

    Definition Classes
    SupportVectorMachineModel → ProbabilisticClassificationModel

  31. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    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

Ungrouped