public final class GISModel extends AbstractModel
AbstractModel.ModelType| 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,
int correctionConstant,
double correctionParam)
Deprecated.
|
GISModel(Context[] params,
String[] predLabels,
String[] outcomeNames,
int correctionConstant,
double correctionParam,
Prior prior)
Deprecated.
|
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 | Method and Description |
|---|---|
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.
|
equals, getAllOutcomes, getBestOutcome, getDataStructures, getIndex, getModelType, getNumOutcomes, getOutcome, hashCode@Deprecated 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)
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.@Deprecated 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.public GISModel(Context[] params, String[] predLabels, String[] outcomeNames, 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.prior - The prior to be used with this model.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)
MaxentModelcontext - 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)
MaxentModelcontext - 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.Copyright © 2017 The Apache Software Foundation. All rights reserved.