opennlp.tools.ml.maxent.quasinewton

Class QNModel

java.lang.Object

opennlp.tools.ml.model.AbstractModel

opennlp.tools.ml.maxent.quasinewton.QNModel

All Implemented Interfaces:

MaxentModel

public class QNModel
extends AbstractModel

Nested Class Summary

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

AbstractModel.ModelType

Constructor Summary

Constructors

Constructor and Description
QNModel(Context[] params, java.lang.String[] predLabels, java.lang.String[] outcomeNames)

Method Summary

Modifier and Type	Method and Description
boolean	equals(java.lang.Object obj)
static double[]	eval(int[] context, float[] values, double[] probs, int nOutcomes, int nPredLabels, double[] parameters) Model evaluation which should be used during training to report model accuracy.
double[]	eval(java.lang.String[] context) Evaluates a context.
double[]	eval(java.lang.String[] context, double[] probs) Evaluates a context.
double[]	eval(java.lang.String[] context, float[] values) Evaluates a contexts with the specified context values.
int	getNumOutcomes() Returns the number of outcomes for this model.

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

getAllOutcomes, getBestOutcome, getDataStructures, getIndex, getModelType, getOutcome

Methods inherited from class java.lang.Object

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

Constructor Detail

QNModel

public QNModel(Context[] params,
               java.lang.String[] predLabels,
               java.lang.String[] outcomeNames)

Method Detail

getNumOutcomes

public int getNumOutcomes()

Description copied from interface: MaxentModel

Returns the number of outcomes for this model.

Specified by:

getNumOutcomes in interface MaxentModel

Overrides:

getNumOutcomes in class AbstractModel

Returns:

The number of outcomes.

eval

public double[] eval(java.lang.String[] context)

Description copied from interface: MaxentModel

Evaluates a context.

Parameters:

context - A list of String names of the contextual predicates which are to be evaluated together.

Returns:

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

eval

public double[] eval(java.lang.String[] context,
                     double[] probs)

Description copied from interface: MaxentModel

Evaluates a context.

Parameters:

context - A list of String names of the contextual predicates which are to be evaluated together.

probs - 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(java.lang.String[] context,
                     float[] values)

Description copied from interface: MaxentModel

Evaluates a contexts with the specified context values.

Parameters:

context - A list 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 static double[] eval(int[] context,
                            float[] values,
                            double[] probs,
                            int nOutcomes,
                            int nPredLabels,
                            double[] parameters)

Model evaluation which should be used during training to report model accuracy.

Parameters:

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

values - Weights of the predicates which have been observed at the present decision point.

probs - Probability for outcomes

nOutcomes - Number of outcomes

nPredLabels - Number of unique predicates

parameters - Model parameters

Returns:

Normalized probabilities for the outcomes given the context.

equals

public boolean equals(java.lang.Object obj)

Overrides:

equals in class java.lang.Object