cc.factorie.app.classify.backend

LinearMulticlassTrainer

class LinearMulticlassTrainer extends MulticlassClassifierTrainer[LinearMulticlassClassifier] with OptimizingBaseLinearTrainer[la.Tensor1, la.Tensor1, Int, LinearMulticlassClassifier]

Linear Supertypes
OptimizingBaseLinearTrainer[la.Tensor1, la.Tensor1, Int, LinearMulticlassClassifier], MulticlassClassifierTrainer[LinearMulticlassClassifier], BaseLinearTrainer[la.Tensor1, la.Tensor1, Int, LinearMulticlassClassifier], AnyRef, Any
Known Subclasses
BatchLinearMulticlassTrainer, OnlineLinearMulticlassTrainer
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Inherited
  1. LinearMulticlassTrainer
  2. OptimizingBaseLinearTrainer
  3. MulticlassClassifierTrainer
  4. BaseLinearTrainer
  5. AnyRef
  6. Any
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Instance Constructors

  1. new LinearMulticlassTrainer(optimizer: GradientOptimizer, useParallelTrainer: Boolean, useOnlineTrainer: Boolean, objective: Multiclass, maxIterations: Int, miniBatch: Int, nThreads: Int)(implicit random: Random)

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. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  7. final def baseTrain(classifier: LinearMulticlassClassifier, labels: Seq[Int], features: Seq[la.Tensor1], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): Unit

    Estimate the parameters of a classifier that has already been created.

    Estimate the parameters of a classifier that has already been created.

    Definition Classes
    OptimizingBaseLinearTrainer → BaseLinearTrainer

  8. def clone(): AnyRef

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

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

    Definition Classes
    AnyRef

  10. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  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 hashCode(): Int

    Definition Classes
    AnyRef → Any

  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  15. val maxIterations: Int

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

  16. val miniBatch: Int

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

  17. val nThreads: Int

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

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

    Definition Classes
    AnyRef

  19. def newModel(featureSize: Int, labelSize: Int): LinearMulticlassClassifier

    Definition Classes
    LinearMulticlassTrainer → BaseLinearTrainer

  20. final def notify(): Unit

    Definition Classes
    AnyRef

  21. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  22. val objective: Multiclass

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

  23. val optimizer: GradientOptimizer

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

  24. implicit val random: Random

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

  25. final def simpleTrain(labelSize: Int, featureSize: Int, labels: Seq[Int], features: Seq[la.Tensor1], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): LinearMulticlassClassifier

    Create a Classifier and estimate its parameters.

    Create a Classifier and estimate its parameters.

    Definition Classes
    BaseLinearTrainer

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

    Definition Classes
    AnyRef

  27. def toString(): String

    Definition Classes
    AnyRef → Any

  28. def train[Label <: LabeledDiscreteVar](classifier: LinearMulticlassClassifier, labels: Seq[Label], l2f: (Label) ⇒ VectorVar, l2w: (Label) ⇒ Double): Unit

    Definition Classes
    MulticlassClassifierTrainer

  29. def train[Label <: LabeledDiscreteVar](classifier: LinearMulticlassClassifier, labels: Seq[Label], l2f: (Label) ⇒ VectorVar, testLabels: Seq[Label], l2w: (Label) ⇒ Double = (l: Label) => 1.0): Unit

    Definition Classes
    MulticlassClassifierTrainer

  30. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], evaluate: (LinearMulticlassClassifier) ⇒ Unit): Unit

    Definition Classes
    MulticlassClassifierTrainer

  31. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): Unit

    Definition Classes
    MulticlassClassifierTrainer

  32. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  33. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  34. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  35. def train(classifier: LinearMulticlassClassifier, labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): Unit

    Definition Classes
    MulticlassClassifierTrainer

  36. def train[Label <: LabeledDiscreteVar](labels: Seq[Label], l2f: (Label) ⇒ VectorVar, l2w: (Label) ⇒ Double): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  37. def train[Label <: LabeledDiscreteVar](labels: Seq[Label], l2f: (Label) ⇒ VectorVar, testLabels: Seq[Label], l2w: (Label) ⇒ Double = (l: Label) => 1.0): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  38. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], evaluate: (LinearMulticlassClassifier) ⇒ Unit): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  39. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], evaluate: (LinearMulticlassClassifier) ⇒ Unit): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  40. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar]): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  41. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double]): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  42. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  43. def train(labels: Seq[LabeledDiscreteVar], features: Seq[VectorVar], weights: Seq[Double], testLabels: Seq[LabeledDiscreteVar], testFeatures: Seq[TensorVar]): LinearMulticlassClassifier

    Definition Classes
    MulticlassClassifierTrainer

  44. val useOnlineTrainer: Boolean

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

  45. val useParallelTrainer: Boolean

    Definition Classes
    LinearMulticlassTrainer → OptimizingBaseLinearTrainer

  46. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from OptimizingBaseLinearTrainer[la.Tensor1, la.Tensor1, Int, LinearMulticlassClassifier]

Inherited from MulticlassClassifierTrainer[LinearMulticlassClassifier]

Inherited from BaseLinearTrainer[la.Tensor1, la.Tensor1, Int, LinearMulticlassClassifier]

Inherited from AnyRef

Inherited from Any

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