Class

epic.preprocess.MLSentenceSegmenter

ClassificationModel

Related Doc: package MLSentenceSegmenter

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class ClassificationModel extends Model[SentenceDecisionInstance]

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Instance Constructors

  1. new ClassificationModel(featureIndex: Index[Feature])

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Type Members

  1. type ExpectedCounts = StandardExpectedCounts[Feature]

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    Definition Classes
    ModelModel
  2. type Inference = ClassificationInference

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    Definition Classes
    ClassificationModelModel
  3. type Marginal = MLSentenceSegmenter.Marginal

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    Definition Classes
    ClassificationModelModel
  4. type Scorer = ClassificationInference

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    Definition Classes
    ClassificationModelModel

Value Members

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

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  2. final def ##(): Int

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

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    Definition Classes
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  4. def accumulateCounts(inf: Inference, s: Scorer, d: SentenceDecisionInstance, m: Marginal, accum: ExpectedCounts, scale: Double): Unit

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    Definition Classes
    ClassificationModelModel
  5. final def accumulateCounts(inf: Inference, d: SentenceDecisionInstance, accum: ExpectedCounts, scale: Double): Unit

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    Definition Classes
    Model
  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  7. def cacheFeatureWeights(weights: DenseVector[Double], suffix: String = ""): Unit

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    Caches the weights using the cache broker.

    Caches the weights using the cache broker.

    Definition Classes
    Model
  8. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
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    Annotations
    @throws( ... )
  9. def emptyCounts: StandardExpectedCounts[Feature]

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    Definition Classes
    ModelModel
  10. final def eq(arg0: AnyRef): Boolean

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

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    Definition Classes
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  12. final def expectedCounts(inf: Inference, d: SentenceDecisionInstance, scale: Double = 1.0): ExpectedCounts

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    Definition Classes
    Model
  13. def expectedCountsToObjective(ecounts: ExpectedCounts): (Double, DenseVector[Double])

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    Definition Classes
    ModelModel
  14. val featureIndex: Index[Feature]

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    Models have features, and this defines the mapping from indices in the weight vector to features.

    Models have features, and this defines the mapping from indices in the weight vector to features.

    Definition Classes
    ClassificationModelModel
  15. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  16. final def getClass(): Class[_]

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  17. def hashCode(): Int

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    Definition Classes
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  18. def inferenceFromWeights(weights: DenseVector[Double]): Inference

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    Definition Classes
    ClassificationModelModel
  19. def initialValueForFeature(f: Feature): Double

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    Definition Classes
    ClassificationModelModel
  20. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  21. def logger: Logger

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    Definition Classes
    SafeLogging
  22. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
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  23. final def notify(): Unit

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    Definition Classes
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  24. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  25. def numFeatures: Int

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    Definition Classes
    Model
  26. def readCachedFeatureWeights(suffix: String = ""): Option[DenseVector[Double]]

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    just saves feature weights to disk as a serialized counter.

    just saves feature weights to disk as a serialized counter. The file is prefix.ser.gz

    Definition Classes
    Model
  27. final def synchronized[T0](arg0: ⇒ T0): T0

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  28. def toString(): String

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  29. final def wait(): Unit

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    @throws( ... )
  30. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )
  31. final def wait(arg0: Long): Unit

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    Definition Classes
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    @throws( ... )
  32. def weightsCacheName: String

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    Attributes
    protected
    Definition Classes
    Model

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