t

epic.framework

EvaluableModel

trait EvaluableModel[Datum] extends Model[Datum]

A model that has some kind of evaluation function. Used with an epic.framework.AnnotatingInference, you can make predictions for a test set and then get the performance.

Self Type
EvaluableModel[Datum]
Linear Supertypes
Model[Datum], SerializableLogging, Serializable, Serializable, AnyRef, Any
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Inherited
  1. EvaluableModel
  2. Model
  3. SerializableLogging
  4. Serializable
  5. Serializable
  6. AnyRef
  7. Any
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Visibility
  1. Public
  2. All

Type Members

  1. abstract type EvaluationResult <: framework.EvaluationResult[EvaluationResult]
  2. abstract type ExpectedCounts >: Null <: framework.ExpectedCounts[ExpectedCounts]
    Definition Classes
    Model
  3. abstract type Inference <: AnnotatingInference[Datum] { ... /* 2 definitions in type refinement */ }
    Definition Classes
    EvaluableModel → Model
  4. abstract type Marginal <: framework.Marginal
    Definition Classes
    Model
  5. abstract type Scorer
    Definition Classes
    Model

Abstract Value Members

  1. abstract def accumulateCounts(inf: Inference, s: Scorer, d: Datum, m: Marginal, accum: ExpectedCounts, scale: Double): Unit
    Definition Classes
    Model
  2. abstract def emptyCounts: ExpectedCounts
    Definition Classes
    Model
  3. abstract def evaluate(guess: Datum, gold: Datum, logResults: Boolean): EvaluationResult
  4. abstract def expectedCountsToObjective(ecounts: ExpectedCounts): (Double, DenseVector[Double])
    Definition Classes
    Model
  5. abstract def featureIndex: Index[Feature]

    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
    Model
  6. abstract def inferenceFromWeights(weights: DenseVector[Double]): Inference
    Definition Classes
    Model
  7. abstract def initialValueForFeature(f: Feature): Double
    Definition Classes
    Model

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def accumulateCounts(inf: Inference, d: Datum, accum: ExpectedCounts, scale: Double): Unit
    Definition Classes
    Model
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def cacheFeatureWeights(weights: DenseVector[Double], suffix: String = ""): Unit

    Caches the weights using the cache broker.

    Caches the weights using the cache broker.

    Definition Classes
    Model
  7. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  10. def evaluate(data: IndexedSeq[Datum], weights: DenseVector[Double], logResults: Boolean = true): EvaluationResult
  11. final def expectedCounts(inf: Inference, d: Datum, scale: Double = 1.0): ExpectedCounts
    Definition Classes
    Model
  12. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  14. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  15. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  16. def logger: LazyLogger
    Attributes
    protected
    Definition Classes
    SerializableLogging
  17. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. final def notify(): Unit
    Definition Classes
    AnyRef
  19. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  20. def numFeatures: Int
    Definition Classes
    Model
  21. def readCachedFeatureWeights(suffix: String = ""): Option[DenseVector[Double]]

    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
  22. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  23. def toString(): String
    Definition Classes
    AnyRef → Any
  24. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  26. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. def weightsCacheName: String
    Attributes
    protected
    Definition Classes
    Model

Inherited from Model[Datum]

Inherited from SerializableLogging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped