Package opennlp.tools.ml.maxent

Klasse GISModel

java.lang.Object

opennlp.tools.ml.model.AbstractModel

opennlp.tools.ml.maxent.GISModel

Alle implementierten Schnittstellen:

MaxentModel

public final class GISModel
extends AbstractModel

A maximum entropy model which has been trained using the Generalized Iterative Scaling (GIS) procedure.

Siehe auch:

• AbstractModel

Verschachtelte Klassen - Übersicht

Von Klasse geerbte verschachtelte Klassen/Schnittstellen opennlp.tools.ml.model.AbstractModel

AbstractModel.ModelType

Konstruktorübersicht

Konstruktoren

Konstruktor	Beschreibung
GISModel(Context[] params, String[] predLabels, String[] outcomeNames)	Initializes a GISModel with the specified parameters, outcome names, and predicate/feature labels.
GISModel(Context[] params, String[] predLabels, String[] outcomeNames, Prior prior)	Initializes a GISModel with the specified parameters, outcome names, and predicate/feature labels.

Methodenübersicht

Modifizierer und Typ	Methode	Beschreibung
boolean	equals(Object obj)
static double[]	eval(int[] context, double[] prior, EvalParameters model)	Evaluates a context and return an array of the likelihood of each outcome given the specified context and the specified parameters.
double[]	eval(String[] context)	Evaluates a context and return an array of the likelihood of each outcome given that context.
double[]	eval(String[] context, double[] outsums)	Evaluates a context.
double[]	eval(String[] context, float[] values)	Evaluates a context with the specified context values.
double[]	eval(String[] context, float[] values, double[] outsums)	Evaluates a context and return an array of the likelihood of each outcome given that context.
int	hashCode()

Von Klasse geerbte Methoden opennlp.tools.ml.model.AbstractModel

getAllOutcomes, getBestOutcome, getDataStructures, getIndex, getModelType, getNumOutcomes, getOutcome

Von Klasse geerbte Methoden java.lang.Object

getClass, notify, notifyAll, toString, wait, wait, wait

Konstruktordetails

GISModel

public GISModel(Context[] params,
 String[] predLabels,
 String[] outcomeNames)

Initializes a GISModel with the specified parameters, outcome names, and predicate/feature labels.

Parameter:

params - The parameters of the model.

predLabels - The names of the predicates used in this model.

outcomeNames - The names of the outcomes this model predicts.

GISModel

public GISModel(Context[] params,
 String[] predLabels,
 String[] outcomeNames,
 Prior prior)

Initializes a GISModel with the specified parameters, outcome names, and predicate/feature labels.

Parameter:

params - The parameters of the model.

predLabels - The names of the predicates used in this model.

outcomeNames - The names of the outcomes this model predicts.

prior - The Prior to be used with this model.

Methodendetails

eval

public double[] eval(String[] context)

Evaluates a context and return an array of the likelihood of each outcome given that context.

Parameter:

context - The names of the predicates which have been observed at the present decision point.

Gibt zurück:

The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method AbstractModel.getOutcome(int).

eval

public double[] eval(String[] context,
 float[] values)

Evaluates a context with the specified context values.

Parameter:

context - An array of String names of the contextual predicates which are to be evaluated together.

values - The values associated with each context.

Gibt zurück:

An array of the probabilities for each of the different outcomes, all of which sum to 1.

eval

public double[] eval(String[] context,
 double[] outsums)

Evaluates a context.

Parameter:

context - An array of String names of the contextual predicates which are to be evaluated together.

outsums - An array which is populated with the probabilities for each of the different outcomes, all of which sum to 1.

Gibt zurück:

An array of the probabilities for each of the different outcomes, all of which sum to 1.

eval

public double[] eval(String[] context,
 float[] values,
 double[] outsums)

Evaluates a context and return an array of the likelihood of each outcome given that context.

Parameter:

context - The names of the predicates which have been observed at the present decision point.

outsums - This is where the distribution is stored.

Gibt zurück:

The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method AbstractModel.getOutcome(int).

eval

public static double[] eval(int[] context,
 double[] prior,
 EvalParameters model)

Evaluates a context and return an array of the likelihood of each outcome given the specified context and the specified parameters.

Parameter:

context - The integer values of the predicates which have been observed at the present decision point.

prior - The prior distribution for the specified context.

model - The set of parameters used in this computation.

Gibt zurück:

The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method AbstractModel.getOutcome(int).

hashCode

public int hashCode()

Setzt außer Kraft:

hashCode in Klasse AbstractModel

equals

public boolean equals(Object obj)

Setzt außer Kraft:

equals in Klasse AbstractModel