|
Oracle Fusion Middleware Java API Reference for Oracle Real-Time Decisions 11g Release 1 (11.1.1) E17787-01 |
|||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface PredictorInterface
Used by ILS code to query Prediction Models.
Method Summary | |
---|---|
void |
flushLearningBuffer() Flushes learning buffers |
int |
getApplicationMappingId() |
void |
getExpectedValues(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray values) Returns predicted numeric values for a set of values of partitioning attributes specified by an output filter. |
void |
getExpectedValues(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray values, SDDoubleArray standardDeviations) Returns predicted numeric values and their standard deviations for a set of values of partitioning attributes specified by an output filter. |
void |
getLikelihoods(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray likelihoods, boolean relaxed) Returns predicted likelihoods for a set of values of target and partitioning attributes specified by an output filter. |
void |
getLikelihoods(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray likelihoods, SDDoubleArray standardDeviations, boolean relaxed) Returns predicted likelihoods for a set of values of target and partitioning attributes specified by an output filter. |
int |
getModelCount(ModelInterface model, ValueFilter[] outputFilter, ModelCount modelCount) |
float |
getModelError(ModelInterface model, ValueFilter[] outputFilter, ModelError modelError) |
float |
getModelLift(ModelInterface model, ValueFilter[] outputFilter, ModelLift modelLift) |
float |
getModelQuality(ModelInterface model, ValueFilter[] outputFilter) |
void |
getMostLikelyValues(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, int outputAttributeId, int n, SDStringArray values, SDDoubleArray likelihoods) Returns predicted most likely values of a given attribute. |
java.lang.String |
getStudyName() |
PredictionContribution[][] |
getWhy(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, int topN) Returns a list of attribute values that contribute the most to the model score. |
void |
learn(ModelInterface[] models, InputProvider inputProvider, LearningRecordWriterFactoryInterface learningRecordWriterFactory, long msTimestamp) Supplies learning information to the Prediction Engine. |
void |
learn(ModelInterface[] models, InputProvider inputProvider, long msTimestamp) Supplies learning information to the Prediction Engine. |
void |
learn(ModelInterface[] models, InputProvider inputProvider, SessionInterface session, long msTimestamp) Supplies learning information to the Prediction Engine. |
void |
loadModels() Loads new models if available. |
ValueFilter[] |
makeExplicitFilter(ModelInterface model, ValueFilter[] filter) Creates an explicit representation of a filter by filling in missing values, numeric intervals and missing sub-filters. |
Method Detail |
---|
void getLikelihoods(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray likelihoods, boolean relaxed)
model
- a model object in the application.input
- an input provider object.outputFilter
- a filter specifying what predictions are requested.likelihoods
- an array of predicted likelihoods.relaxed
- if this flag is true
, then the model will return a likelihood prediction even if the prediction accuracy is very low. Otherwise, when prediction accuracy is low, the model will return Double.NaN.void getLikelihoods(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray likelihoods, SDDoubleArray standardDeviations, boolean relaxed)
model
- a model object in the application.input
- an input provider object.outputFilter
- a filter specifying what predictions are requested.likelihoods
- output an array of predicted likelihoods.standardDeviations
- output an array of estimated standard deviations of likelihoods.relaxed
- if this flag is true
, then the model will return a likelihood prediction even if the prediction accuracy is very low. Otherwise, when prediction accuracy is low, the model will return Double.NaN.PredictionContribution[][] getWhy(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, int topN)
model
- a model object in the application.input
- an input provider object.outputFilter
- a filter specifying what predictions are requested.topN
- number of top input score contributions to return.void getExpectedValues(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray values)
model
- a model object in the application.input
- an input provider object.outputFilter
- a filter specifying what predictions are requested.values
- an array of predicted expected values.void getExpectedValues(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, SDDoubleArray values, SDDoubleArray standardDeviations)
model
- a model object in the application.input
- an input provider object.outputFilter
- a filter specifying what predictions are requested.values
- an array of predicted expected values.standardDeviations
- an array of predicted standard deviations.void getMostLikelyValues(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, int outputAttributeId, int n, SDStringArray values, SDDoubleArray likelihoods)
model
- a model object in the application.input
- an input provider object.outputFilter
- a filter specifying what predictions are requested.outputAttributeId
- ID of an attribute to return most likely values for.n
- a requested number of most likely values.values
- an array of returned most likely values.ValueFilter[] makeExplicitFilter(ModelInterface model, ValueFilter[] filter)
model
- a model object in the application.filter
- a filter to make explicit. This object is not changed by the method.void learn(ModelInterface[] models, InputProvider inputProvider, long msTimestamp)
models
- an array of models that the learning applies to.inputProvider
- an input provider object responsible for providing values of input, partitioning and target attributes except the ones provided by the model object themselves.msTimestamp
- timestamp in milliseconds.void flushLearningBuffer()
void loadModels()
java.lang.String getStudyName()
int getApplicationMappingId()
void learn(ModelInterface[] models, InputProvider inputProvider, LearningRecordWriterFactoryInterface learningRecordWriterFactory, long msTimestamp)
models
- an array of models that the learning applies to.inputProvider
- an input provider object responsible for providing values of input, partitioning and target attributes except the ones provided by the model object themselves.learningRecordWriterFactory
- used to write learning records either with autoFlush (for interactive sessions) or with manual flush (for batch sessions).msTimestamp
- timestamp in milliseconds.void learn(ModelInterface[] models, InputProvider inputProvider, SessionInterface session, long msTimestamp)
Called from generated code.
models
- an array of models that the learning applies to.inputProvider
- an input provider object responsible for providing values of input, partitioning and target attributes except the ones provided by the model object themselves.session
- Contains a factory used to write learning records either directly to the learning table (for interactive sessions) or to the batch frameworks learning sandbox (for batch sessions).msTimestamp
- timestamp in milliseconds.int getModelCount(ModelInterface model, ValueFilter[] outputFilter, ModelCount modelCount)
ChoiceModelInterface.getChoiceModelCount(ModelCount, String)
, ChoiceEventModelInterface.getChoiceEventModelCount(ModelCount, String, String)
float getModelQuality(ModelInterface model, ValueFilter[] outputFilter)
ChoiceModelInterface.getChoiceModelQuality(String)
, ChoiceEventModelInterface.getChoiceEventModelQuality(String, String)
float getModelLift(ModelInterface model, ValueFilter[] outputFilter, ModelLift modelLift)
ChoiceModelInterface.getChoiceModelLift(ModelLift, String)
, ChoiceEventModelInterface.getChoiceEventModelLift(ModelLift, String, String)
float getModelError(ModelInterface model, ValueFilter[] outputFilter, ModelError modelError)
ChoiceModelInterface.getChoiceModelError(ModelError, String)
, ChoiceEventModelInterface.getChoiceEventModelError(ModelError, String, String)
|
Oracle Fusion Middleware Java API Reference for Oracle Real-Time Decisions 11g Release 1 (11.1.1) E17787-01 |
|||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |