Package | Description |
---|---|
opennlp.tools.ml.maxent |
Provides main functionality of the maxent package including data structures and
algorithms for parameter estimation.
|
opennlp.tools.ml.maxent.io |
Provides the I/O functionality of the maxent package including reading
and writing models in several formats.
|
opennlp.tools.ml.maxent.quasinewton | |
opennlp.tools.ml.model | |
opennlp.tools.ml.naivebayes | |
opennlp.tools.ml.perceptron |
Constructor and Description |
---|
GISModel(Context[] params,
String[] predLabels,
String[] outcomeNames)
Creates a new model with the specified parameters, outcome names, and
predicate/feature labels.
|
GISModel(Context[] params,
String[] predLabels,
String[] outcomeNames,
Prior prior)
Creates a new model with the specified parameters, outcome names, and
predicate/feature labels.
|
Modifier and Type | Field and Description |
---|---|
protected Context[] |
GISModelWriter.PARAMS |
Constructor and Description |
---|
QNModel(Context[] params,
String[] predLabels,
String[] outcomeNames) |
Modifier and Type | Class and Description |
---|---|
class |
MutableContext
Class used to store parameters or expected values associated with this context which
can be updated or assigned.
|
Modifier and Type | Field and Description |
---|---|
protected Map<String,Context> |
AbstractModel.pmap
Mapping between predicates/contexts and an integer representing them.
|
Modifier and Type | Method and Description |
---|---|
protected Context[] |
AbstractModelReader.getParameters(int[][] outcomePatterns)
Reads the parameters from a file and populates an array of context objects.
|
Context[] |
EvalParameters.getParams() |
Context[] |
DynamicEvalParameters.getParams() |
Modifier and Type | Method and Description |
---|---|
void |
UniformPrior.logPrior(double[] dist,
Context[] context,
float[] values) |
void |
Prior.logPrior(double[] dist,
Context[] context,
float[] values)
Populates the specified array with the the log of the distribution for the specified context.
|
Constructor and Description |
---|
AbstractModel(Context[] params,
String[] predLabels,
Map<String,Context> pmap,
String[] outcomeNames) |
AbstractModel(Context[] params,
String[] predLabels,
String[] outcomeNames) |
EvalParameters(Context[] params,
int numOutcomes) |
Constructor and Description |
---|
AbstractModel(Context[] params,
String[] predLabels,
Map<String,Context> pmap,
String[] outcomeNames) |
DynamicEvalParameters(List<? extends Context> params,
int numOutcomes)
Creates a set of paramters which can be evaulated with the eval method.
|
Modifier and Type | Field and Description |
---|---|
protected Context[] |
NaiveBayesModelWriter.PARAMS |
Modifier and Type | Method and Description |
---|---|
protected double[] |
NaiveBayesModel.initOutcomeTotals(String[] outcomeNames,
Context[] params) |
Constructor and Description |
---|
NaiveBayesEvalParameters(Context[] params,
int numOutcomes,
double[] outcomeTotals,
long vocabulary) |
NaiveBayesModel(Context[] params,
String[] predLabels,
String[] outcomeNames) |
Modifier and Type | Field and Description |
---|---|
protected Context[] |
PerceptronModelWriter.PARAMS |
Constructor and Description |
---|
PerceptronModel(Context[] params,
String[] predLabels,
String[] outcomeNames) |
Copyright © 2017 The Apache Software Foundation. All rights reserved.