trait
EvaluableModel[Datum] extends Model[Datum]
Type Members
-
-
-
abstract
type
Inference <: AnnotatingInference[Datum] { ... /* 2 definitions in type refinement */ }
-
-
abstract
type
Scorer
Abstract Value Members
-
abstract
def
accumulateCounts(inf: Inference, s: Scorer, d: Datum, m: Marginal, accum: ExpectedCounts, scale: Double): Unit
-
-
abstract
def
evaluate(guess: Datum, gold: Datum, logResults: Boolean): EvaluationResult
-
abstract
def
expectedCountsToObjective(ecounts: ExpectedCounts): (Double, DenseVector[Double])
-
abstract
def
featureIndex: Index[Feature]
-
abstract
def
inferenceFromWeights(weights: DenseVector[Double]): Inference
-
abstract
def
initialValueForFeature(f: Feature): Double
Concrete Value Members
-
final
def
!=(arg0: AnyRef): Boolean
-
final
def
!=(arg0: Any): Boolean
-
final
def
##(): Int
-
final
def
==(arg0: AnyRef): Boolean
-
final
def
==(arg0: Any): Boolean
-
final
def
accumulateCounts(inf: Inference, d: Datum, accum: ExpectedCounts, scale: Double): Unit
-
final
def
asInstanceOf[T0]: T0
-
def
cacheFeatureWeights(weights: DenseVector[Double], suffix: String = ""): Unit
-
def
clone(): AnyRef
-
final
def
eq(arg0: AnyRef): Boolean
-
def
equals(arg0: Any): Boolean
-
def
evaluate(data: IndexedSeq[Datum], weights: DenseVector[Double], logResults: Boolean = true): EvaluationResult
-
final
def
expectedCounts(inf: Inference, d: Datum, scale: Double = 1.0): ExpectedCounts
-
def
finalize(): Unit
-
final
def
getClass(): Class[_]
-
def
hashCode(): Int
-
final
def
isInstanceOf[T0]: Boolean
-
def
logger: Logger
-
final
def
ne(arg0: AnyRef): Boolean
-
final
def
notify(): Unit
-
final
def
notifyAll(): Unit
-
def
numFeatures: Int
-
def
readCachedFeatureWeights(suffix: String = ""): Option[DenseVector[Double]]
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
-
def
toString(): String
-
final
def
wait(): Unit
-
final
def
wait(arg0: Long, arg1: Int): Unit
-
final
def
wait(arg0: Long): Unit
-
def
weightsCacheName: String
Inherited from Model[Datum]
Inherited from AnyRef
Inherited from Any
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.