Class

com.johnsnowlabs.nlp.annotators.pos.perceptron

TrainingPerceptronLegacy

Related Doc: package perceptron

Permalink

class TrainingPerceptronLegacy extends Serializable

Linear Supertypes
Serializable, Serializable, AnyRef, Any
Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. TrainingPerceptronLegacy
  2. Serializable
  3. Serializable
  4. AnyRef
  5. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new TrainingPerceptronLegacy(tags: Array[String], taggedWordBook: Map[String, String], featuresWeight: Map[String, Map[String, Double]], lastIteration: Int = 0)

    Permalink

Value Members

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

    Permalink
    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any

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

    Permalink
    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any

  5. def clone(): AnyRef

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

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

    Permalink
    Definition Classes
    AnyRef

  7. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any

  8. def finalize(): Unit

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

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

    Permalink
    Definition Classes
    AnyRef → Any

  10. def getWeights: Map[String, Map[String, Double]]

    Permalink

  11. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any

  12. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any

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

    Permalink
    Definition Classes
    AnyRef

  14. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef

  15. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef

  16. def predict(features: Map[String, Int]): String

    Permalink

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

    Permalink
    Definition Classes
    AnyRef

  18. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any

  19. def update(truth: String, guess: String, features: Map[String, Int]): Unit

    Permalink

    This is model learning tweaking during training, in-place Uses mutable collections since this runs per word, not per iteration Hence, performance is needed, without risk as long as this is a non parallel training running outside spark

  20. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

getParam

Ungrouped