Trait

io.picnicml.doddlemodel.linear.typeclasses

LinearClassifier

Related Doc: package typeclasses

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trait LinearClassifier[A] extends LinearModel[A] with Classifier[A]

Linear Supertypes
Classifier[A], Predictor[A], Estimator[A], LinearModel[A], AnyRef, Any
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  2. By Inheritance
Inherited
  1. LinearClassifier
  2. Classifier
  3. Predictor
  4. Estimator
  5. LinearModel
  6. AnyRef
  7. Any
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Visibility
  1. Public
  2. All

Abstract Value Members

  1. abstract def copy(model: A, numClasses: Int): A

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    A function that creates a new classifier with numClasses set.

    A function that creates a new classifier with numClasses set.

    Attributes
    protected[io.picnicml.doddlemodel]
    Definition Classes
    Classifier
  2. abstract def copy(model: A, w: RealVector): A

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    A function that creates a new linear model with parameters w.

    A function that creates a new linear model with parameters w.

    Attributes
    protected
    Definition Classes
    LinearModel
  3. abstract def lossGradStateless(model: A, w: RealVector, x: Features, y: Target): RealVector

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    A stateless function that calculates the gradient of the loss function wrt.

    A stateless function that calculates the gradient of the loss function wrt. model parameters.

    Attributes
    protected[io.picnicml.doddlemodel.linear]
    Definition Classes
    LinearModel
  4. abstract def lossStateless(model: A, w: RealVector, x: Features, y: Target): Double

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    A stateless function that calculates the value of the loss function.

    A stateless function that calculates the value of the loss function.

    Attributes
    protected[io.picnicml.doddlemodel.linear]
    Definition Classes
    LinearModel
  5. abstract def numClasses(model: A): Option[Int]

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    Definition Classes
    Classifier
  6. abstract def predictProbaStateless(model: A, w: RealVector, x: Features): Simplex

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    A stateless function that predicts probability of each class.

    A stateless function that predicts probability of each class.

    Attributes
    protected
  7. abstract def predictStateless(model: A, w: RealVector, x: Features): Target

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    A stateless function that predicts a target variable.

    A stateless function that predicts a target variable.

    Attributes
    protected
    Definition Classes
    LinearModel
  8. abstract def w(model: A): Option[RealVector]

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    Parameters (weights) of a linear model, i.e.

    Parameters (weights) of a linear model, i.e. the state of the model.

    Attributes
    protected
    Definition Classes
    LinearModel

Concrete 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. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  5. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  9. def fit(model: A, x: Features, y: Target): A

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    Definition Classes
    ClassifierPredictor
  10. def fitSafe(model: A, x: Features, y: Target): A

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    A function that is guaranteed to receive an appropriate target variable when called.

    A function that is guaranteed to receive an appropriate target variable when called. Additionally, the object is guaranteed not to be fitted.

    Attributes
    protected
    Definition Classes
    LinearClassifierClassifier
  11. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  12. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  13. def isFitted(model: A): Boolean

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    Definition Classes
    LinearModel
  14. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  15. def maximumLikelihood(model: A, x: Features, y: Target, init: RealVector): RealVector

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    Attributes
    protected
    Definition Classes
    LinearModel
  16. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  17. final def notify(): Unit

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    Definition Classes
    AnyRef
  18. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  19. def predict(model: A, x: Features): Target

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    Definition Classes
    Predictor
  20. def predictProba(model: A, x: Features): Simplex

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    Definition Classes
    Classifier
  21. def predictProbaSafe(model: A, x: Features): Simplex

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    A function that is guaranteed to be called on a fitted model.

    A function that is guaranteed to be called on a fitted model.

    Attributes
    protected
    Definition Classes
    LinearClassifierClassifier
  22. def predictSafe(model: A, x: Features): Target

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    Definition Classes
    LinearModel
  23. def save(model: A, filePath: String): Unit

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    Definition Classes
    Estimator
  24. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  25. def toString(): String

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    Definition Classes
    AnyRef → Any
  26. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. def xWithBiasTerm(x: Features): Features

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    Attributes
    protected
    Definition Classes
    LinearModel

Inherited from Classifier[A]

Inherited from Predictor[A]

Inherited from Estimator[A]

Inherited from LinearModel[A]

Inherited from AnyRef

Inherited from Any

Ungrouped