Class

ml.combust.mleap.core.classification

ProbabilisticLogisticsRegressionModel

Related Doc: package classification

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case class ProbabilisticLogisticsRegressionModel(coefficientMatrix: Matrix, interceptVector: Vector, thresholds: Option[Array[Double]]) extends AbstractLogisticRegressionModel with Product with Serializable

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

  1. new ProbabilisticLogisticsRegressionModel(coefficientMatrix: Matrix, interceptVector: Vector, thresholds: Option[Array[Double]])

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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 coefficientMatrix: Matrix

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  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 interceptVector: Vector

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  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
    ProbabilisticLogisticsRegressionModel → ProbabilisticClassificationModel

  18. val numFeatures: Int

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    Definition Classes
    ProbabilisticLogisticsRegressionModel → 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
    ProbabilisticLogisticsRegressionModel → 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
    ProbabilisticLogisticsRegressionModel → 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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    Definition Classes
    ProbabilisticLogisticsRegressionModel → 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 Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from AbstractLogisticRegressionModel

Inherited from ProbabilisticClassificationModel

Inherited from ClassificationModel

Inherited from Model

Inherited from AnyRef

Inherited from Any

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