Package opennlp.tools.ml.maxent

Class GISModel

java.lang.Object

opennlp.tools.ml.model.AbstractModel

opennlp.tools.ml.maxent.GISModel

All Implemented Interfaces:

MaxentModel

public final class GISModel
extends AbstractModel

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

See Also:

• AbstractModel

Nested Class Summary

Nested classes/interfaces inherited from class opennlp.tools.ml.model.AbstractModel

AbstractModel.ModelType

Constructor Summary

Constructors

Constructor	Description
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.

Method Summary

Modifier and Type	Method	Description
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()

Methods inherited from class opennlp.tools.ml.model.AbstractModel

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

Methods inherited from class java.lang.Object

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

Constructor Details

GISModel

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

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

Parameters:

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.

Parameters:

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.

Method Details

eval

public double[] eval(String[] context)

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

Parameters:

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

Returns:

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.

Parameters:

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

values - The values associated with each context.

Returns:

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.

Parameters:

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.

Returns:

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.

Parameters:

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

outsums - This is where the distribution is stored.

Returns:

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.

Parameters:

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.

Returns:

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()

Overrides:

hashCode in class AbstractModel

equals

public boolean equals(Object obj)

Overrides:

equals in class AbstractModel