Class/Object

org.clulab.learning

PerceptronClassifier

Related Docs: object PerceptronClassifier | package learning

Permalink

class PerceptronClassifier[L, F] extends Classifier[L, F] with Serializable

Multiclass perceptron classifier, in primal mode Includes averaging, hard margin, burn-in iterations User: mihais Date: 12/15/13

Linear Supertypes
Serializable, Serializable, Classifier[L, F], AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. PerceptronClassifier
  2. Serializable
  3. Serializable
  4. Classifier
  5. AnyRef
  6. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new PerceptronClassifier(props: Properties)

    Permalink

  2. new PerceptronClassifier(epochs: Int = 2, burnInIterations: Int = 0, marginRatio: Double = 1.0)

    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. val burnInIterations: Int

    Permalink

  6. def classOf(d: Datum[L, F]): L

    Permalink

    Returns the argmax for this datum

    Returns the argmax for this datum

    Definition Classes
    PerceptronClassifier → Classifier

  7. def clone(): AnyRef

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

  8. def displayWeights(pw: PrintWriter): Unit

    Permalink

  9. val epochs: Int

    Permalink

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

    Permalink
    Definition Classes
    AnyRef

  11. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any

  12. def finalize(): Unit

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

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

    Permalink
    Definition Classes
    AnyRef → Any

  14. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any

  15. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any

  16. val marginRatio: Double

    Permalink

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

    Permalink
    Definition Classes
    AnyRef

  18. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef

  19. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef

  20. def saveTo(w: Writer): Unit

    Permalink

    Saves to writer.

    Saves to writer. Does NOT close the writer

    Definition Classes
    PerceptronClassifier → Classifier

  21. def saveTo(fileName: String): Unit

    Permalink

    Saves the current model to a file

    Saves the current model to a file

    Definition Classes
    Classifier

  22. def scoresOf(d: Datum[L, F]): Counter[L]

    Permalink

    Returns the scores of all possible labels for this datum Convention: if the classifier can return probabilities, these must be probabilities

    Returns the scores of all possible labels for this datum Convention: if the classifier can return probabilities, these must be probabilities

    Definition Classes
    PerceptronClassifier → Classifier

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

    Permalink
    Definition Classes
    AnyRef

  24. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any

  25. def train(dataset: Dataset[L, F], indices: Array[Int]): Unit

    Permalink

    Trains a classifier, using only the datums specified in indices indices is useful for bagging

    Trains a classifier, using only the datums specified in indices indices is useful for bagging

    Definition Classes
    PerceptronClassifier → Classifier

  26. def train(dataset: Dataset[L, F], spans: Option[Iterable[(Int, Int)]] = None): Unit

    Permalink

    Trains the classifier on the given dataset spans is useful during cross validation

    Trains the classifier on the given dataset spans is useful during cross validation

    Definition Classes
    Classifier

  27. final def wait(): Unit

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

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

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

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

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

Inherited from Serializable

Inherited from Serializable

Inherited from Classifier[L, F]

Inherited from AnyRef

Inherited from Any

Ungrouped