Class NegLogLikelihood

Namespace

NOpenNLP.Tools.Ml.Maxent.Quasinewton

Assembly

NOpenNLP.Tools.dll

Evaluate negative log-likelihood and its gradient from DataIndexer.

public class NegLogLikelihood : IFunction

Inheritance

object

NegLogLikelihood

Implements

IFunction

Derived

ParallelNegLogLikelihood

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

NegLogLikelihood(IDataIndexer)

public NegLogLikelihood(IDataIndexer indexer)

Parameters

indexer IDataIndexer

Fields

contexts

protected readonly int[][] contexts

Field Value

int[][]

dimension

protected int dimension

Field Value

int

expectation

protected double[] expectation

Field Value

double[]

gradient

protected double[] gradient

Field Value

double[]

numContexts

protected int numContexts

Field Value

int

numFeatures

protected int numFeatures

Field Value

int

numOutcomes

protected int numOutcomes

Field Value

int

numTimesEventsSeen

protected readonly int[] numTimesEventsSeen

Field Value

int[]

outcomeList

protected readonly int[] outcomeList

Field Value

int[]

tempSums

protected double[] tempSums

Field Value

double[]

values

protected readonly float[][]? values

Field Value

float[][]

Properties

Dimension

public virtual int Dimension { get; }

Property Value

int

Methods

GetInitialPoint()

public virtual double[] GetInitialPoint()

Returns

double[]

GradientAt(double[])

Compute gradient

public virtual double[] GradientAt(double[] x)

Parameters

x double[]

Returns

double[]

IndexOf(int, int)

protected int IndexOf(int outcomeId, int featureId)

Parameters

outcomeId int

featureId int

Returns

int

ValueAt(double[])

Negative log-likelihood

public virtual double ValueAt(double[] x)

Parameters

x double[]

Returns

double