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java.lang.Objectopennlp.model.AbstractModel
opennlp.maxent.GISModel
public final class GISModel
A maximum entropy model which has been trained using the Generalized Iterative Scaling procedure (implemented in GIS.java).
| Nested Class Summary |
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| Nested classes/interfaces inherited from class opennlp.model.AbstractModel |
|---|
AbstractModel.ModelType |
| Constructor Summary | |
|---|---|
GISModel(Context[] params,
String[] predLabels,
String[] outcomeNames,
int correctionConstant,
double correctionParam)
Creates a new model with the specified parameters, outcome names, and predicate/feature labels. |
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GISModel(Context[] params,
String[] predLabels,
String[] outcomeNames,
int correctionConstant,
double correctionParam,
Prior prior)
Creates a new model with the specified parameters, outcome names, and predicate/feature labels. |
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| Method Summary | |
|---|---|
static double[] |
eval(int[] context,
double[] prior,
EvalParameters model)
Use this model to evaluate a context and return an array of the likelihood of each outcome given the specified context and the specified parameters. |
static double[] |
eval(int[] context,
float[] values,
double[] prior,
EvalParameters model)
Use this model to evaluate a context and return an array of the likelihood of each outcome given the specified context and the specified parameters. |
double[] |
eval(String[] context)
Use this model to evaluate 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 contexts with the specified context values. |
double[] |
eval(String[] context,
float[] values,
double[] outsums)
Use this model to evaluate a context and return an array of the likelihood of each outcome given that context. |
static void |
main(String[] args)
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| Methods inherited from class opennlp.model.AbstractModel |
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getAllOutcomes, getBestOutcome, getDataStructures, getIndex, getModelType, getNumOutcomes, getOutcome |
| Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
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public GISModel(Context[] params,
String[] predLabels,
String[] outcomeNames,
int correctionConstant,
double correctionParam)
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.correctionConstant - The maximum number of active features which occur in an event.correctionParam - The parameter associated with the correction feature.
public GISModel(Context[] params,
String[] predLabels,
String[] outcomeNames,
int correctionConstant,
double correctionParam,
Prior prior)
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.correctionConstant - The maximum number of active features which occur in an event.correctionParam - The parameter associated with the correction feature.prior - The prior to be used with this model.| Method Detail |
|---|
public final double[] eval(String[] context)
context - The names of the predicates which have been observed at the
present decision point.
public final double[] eval(String[] context,
float[] values)
MaxentModel
context - A list of String names of the contextual predicates
which are to be evaluated together.values - The values associated with each context.
public final double[] eval(String[] context,
double[] outsums)
MaxentModel
context - A list 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.
public final double[] eval(String[] context,
float[] values,
double[] outsums)
context - The names of the predicates which have been observed at the
present decision point.outsums - This is where the distribution is stored.
public static double[] eval(int[] context,
double[] prior,
EvalParameters model)
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 parametes used in this computation.
public static double[] eval(int[] context,
float[] values,
double[] prior,
EvalParameters model)
context - The integer values of the predicates which have been observed at
the present decision point.values - The values for each of the parameters.prior - The prior distribution for the specified context.model - The set of parametes used in this computation.
public static void main(String[] args)
throws IOException
IOException
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