abstract
class
MEMMSequenceTagger[L, F] extends SequenceTagger[L, F]
Instance Constructors
-
new
MEMMSequenceTagger(order: Int = 1, leftToRight: Boolean = true)(implicit arg0: ClassTag[L])
Abstract Value Members
-
abstract
def
featureExtractor(features: Counter[F], sentence: Sentence, offset: Int): Unit
-
abstract
def
labelExtractor(sentence: Sentence): Array[L]
-
abstract
def
mkFeatAtBeginSent(position: Int, prefix: String): F
-
abstract
def
mkFeatAtEndSent(position: Int, prefix: String): F
-
abstract
def
mkFeatAtHistory(position: Int, prefix: String, label: L): F
Concrete Value Members
-
final
def
!=(arg0: Any): Boolean
-
final
def
##(): Int
-
final
def
==(arg0: Any): Boolean
-
def
addFirstPassFeatures(features: Counter[F], order: Int, labels: Seq[L], offset: Int): Unit
-
def
addHistoryFeatures(features: Counter[F], order: Int, labels: Seq[L], offset: Int): Unit
-
def
addLeftFeatures(features: Counter[F], order: Int, prefix: String, labels: Seq[L], offset: Int): Unit
-
def
addRightFeatures(features: Counter[F], order: Int, prefix: String, labels: Seq[L], offset: Int): Unit
-
final
def
asInstanceOf[T0]: T0
-
def
classesOf(origSentence: Sentence): Array[L]
-
def
clone(): AnyRef
-
final
def
eq(arg0: AnyRef): Boolean
-
def
equals(arg0: Any): Boolean
-
def
finalize(): Unit
-
def
find(sentence: Sentence): Array[L]
-
final
def
getClass(): Class[_]
-
def
hashCode(): Int
-
final
def
isInstanceOf[T0]: Boolean
-
var
leftToRight: Boolean
-
def
load(reader: BufferedReader): Unit
-
def
loadFromFile(fn: File): Unit
-
def
loadFromResource(rn: String): Unit
-
var
model: Option[Classifier[L, F]]
-
final
def
ne(arg0: AnyRef): Boolean
-
final
def
notify(): Unit
-
final
def
notifyAll(): Unit
-
var
order: Int
-
def
save(fn: File): Unit
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
-
def
toString(): String
-
def
train(docs: Iterator[Document]): Unit
-
final
def
wait(): Unit
-
final
def
wait(arg0: Long, arg1: Int): Unit
-
final
def
wait(arg0: Long): Unit
Inherited from AnyRef
Inherited from Any
Sequence tagger using a maximum entrop Markov model (MEMM) User: mihais Date: 8/26/17