Model

Instance Constructors

new Model(inner: ParserModel[L, W])

Type Members

type ExpectedCounts = StandardExpectedCounts[Feature]

Definition Classes
Model → Model
type Inference = SentimentTreebankPipeline.Inference[L, W]

Definition Classes
Model → Model
type Marginal = ParseMarginal[L, W]

Definition Classes
Model → Model
type Scorer = GrammarAnchoring[L, W]

Definition Classes
Model → Model

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def accumulateCounts(inf: Inference, s: Scorer, d: TreeInstance[L, W], m: Marginal, accum: ExpectedCounts, scale: Double): Unit

Definition Classes
Model → Model
final def accumulateCounts(inf: Inference, d: TreeInstance[L, W], accum: ExpectedCounts, scale: Double): Unit

Definition Classes
Model
final def asInstanceOf[T0]: T0

Definition Classes
Any
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
def clone(): AnyRef

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

Definition Classes
Model → Model
final def eq(arg0: AnyRef): Boolean

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

Definition Classes
AnyRef → Any
final def expectedCounts(inf: Inference, d: TreeInstance[L, W], scale: Double = 1.0): ExpectedCounts

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

Definition Classes
Model → Model
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 → Model
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
Annotations
@HotSpotIntrinsicCandidate()
def hashCode(): Int

Definition Classes
AnyRef → Any
Annotations
@HotSpotIntrinsicCandidate()
def inferenceFromWeights(weights: DenseVector[Double]): Inference

Definition Classes
Model → Model
def initialValueForFeature(f: Feature): Double

Definition Classes
Model → Model
val inner: ParserModel[L, W]
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def logger: LazyLogger

Attributes
protected
Definition Classes
SerializableLogging
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@HotSpotIntrinsicCandidate()
def numFeatures: Int

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

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
def weightsCacheName: String

Attributes
protected
Definition Classes
Model

Deprecated Value Members

def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
Deprecated
(Since version ) see corresponding Javadoc for more information.

Related Doc: package SentimentTreebankPipeline

class Model[L, W] extends framework.Model[TreeInstance[L, W]]

Instance Constructors

new Model(inner: ParserModel[L, W])

Type Members

type ExpectedCounts = StandardExpectedCounts[Feature]

type Inference = SentimentTreebankPipeline.Inference[L, W]

type Marginal = ParseMarginal[L, W]

type Scorer = GrammarAnchoring[L, W]

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def accumulateCounts(inf: Inference, s: Scorer, d: TreeInstance[L, W], m: Marginal, accum: ExpectedCounts, scale: Double): Unit

final def accumulateCounts(inf: Inference, d: TreeInstance[L, W], accum: ExpectedCounts, scale: Double): Unit

final def asInstanceOf[T0]: T0

def cacheFeatureWeights(weights: DenseVector[Double], suffix: String = ""): Unit

def clone(): AnyRef

def emptyCounts: StandardExpectedCounts[Feature]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

final def expectedCounts(inf: Inference, d: TreeInstance[L, W], scale: Double = 1.0): ExpectedCounts

def expectedCountsToObjective(ecounts: ExpectedCounts): (Double, DenseVector[Double])

def featureIndex: Index[Feature]

final def getClass(): Class[_]

def hashCode(): Int

def inferenceFromWeights(weights: DenseVector[Double]): Inference

def initialValueForFeature(f: Feature): Double

val inner: ParserModel[L, W]

final def isInstanceOf[T0]: Boolean

def logger: LazyLogger

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(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

final def wait(): Unit

def weightsCacheName: String

Deprecated Value Members

def finalize(): Unit

Inherited from framework.Model[TreeInstance[L, W]]

Inherited from SerializableLogging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped