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Uses of Class
com.sigmadynamics.server.rtis.PredictionEngine.ValueFilter

Packages that use ValueFilter

com.sigmadynamics.server.rtis.PredictionEngine

Platform support for prediction models.

Uses of ValueFilter in com.sigmadynamics.server.rtis.PredictionEngine

Subclasses of ValueFilter in com.sigmadynamics.server.rtis.PredictionEngine

class	DiscreteValueFilter Used in querying Prediction Models for filtering discrete attributes.
class	NumericValueFilter Filter for numeric values.

Methods in com.sigmadynamics.server.rtis.PredictionEngine that return ValueFilter

ValueFilter[]

PredictorInterface.makeExplicitFilter(ModelInterface model, ValueFilter[] filter) Creates an explicit representation of a filter by filling in missing values, numeric intervals and missing sub-filters.

Methods in com.sigmadynamics.server.rtis.PredictionEngine with parameters of type ValueFilter

void	PredictorInterface.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	PredictorInterface.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	PredictorInterface.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	PredictorInterface.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	PredictorInterface.getModelCount(ModelInterface model, ValueFilter[] outputFilter, ModelCount modelCount)
float	PredictorInterface.getModelError(ModelInterface model, ValueFilter[] outputFilter, ModelError modelError)
float	PredictorInterface.getModelLift(ModelInterface model, ValueFilter[] outputFilter, ModelLift modelLift)
float	PredictorInterface.getModelQuality(ModelInterface model, ValueFilter[] outputFilter)
void	PredictorInterface.getMostLikelyValues(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, int outputAttributeId, int n, SDStringArray values, SDDoubleArray likelihoods) Returns predicted most likely values of a given attribute.
PredictionContribution[][]	PredictorInterface.getWhy(ModelInterface model, InputProvider input, ValueFilter[] outputFilter, int topN) Returns a list of attribute values that contribute the most to the model score.
ValueFilter[]	PredictorInterface.makeExplicitFilter(ModelInterface model, ValueFilter[] filter) Creates an explicit representation of a filter by filling in missing values, numeric intervals and missing sub-filters.

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