oracle.dmt.jdm.algorithm.abn
Interface OraABNSettings

All Superinterfaces:

javax.datamining.base.AlgorithmSettings, javax.datamining.supervised.SupervisedAlgorithmSettings

public interface OraABNSettings

extends javax.datamining.supervised.SupervisedAlgorithmSettings

An instance of OraABNSettings is used to specify settings for the Adaptive Bayes Network algorithm. The settings are intended to allow the user control over build performance. The build process includes a step that finds an array of seed features. A seed feature consists of a training attribute that is statistically correlated with the target. In a training table with many attributes, many seed features may be found. The statistical procedure ranks the seed features with respect to their statistical correlation. The first step consists of constructing a Naive Bayes Model of size specified by numberOfPredictorsInNBModel parameter consisting of the top ranked attributes. Subsequent steps extend each seed feature one at a time in rank order. The maximum number of seed features extended is specified by maximum predictors. Each step must yield a model of smaller description length or it is rejected. The initial baseline is the global target distribution or prior. Each time a seed feature is extended, it involves a scan of the table.

To control the length of time it takes for the build, there are three user parameters:

• MaximumPredictors - the maximum number of predictors is a feature selection mechanism that can provide a substantial performance improvement, especially in the instance of wide training tables. Note that the predictors are rank ordered with respect to an MDL measure of their correlation to the target which is a greedy measure of their likelihood of being incorporated into the model. The actual number of predictors will be the minimum of the parameter value and the number of active predictors in the model. If the value is less than the number of active predictors in the model, the predictors are chosen in accordance with their MDL rank. Default is 25. The number of predictors in the baseline Naive Bayes model is restricted by another mechanism: numberOfPredictorsInNBModel, which can be more or less than MaximumPredictors.
• numberOfPredictorsInNBModel - the number of predictors in the NB model. The actual number of predictors will be the minimum of the parameter value and the number of active predictors in the model. If the value is less than the number of active predictors in the model, the predictors are chosen in accordance with their MDL rank. Default is 10.
• This setting is ignored if the model type is neither NaiveBayesBuild nor MultiFeatureBuild.
• ModelBuildType - indicates what model types (MultiFeatureBuild, SingleFeatureBuild, or NaiveBayesBuild) to be built. Default is MultiFeatureBuild.

See Also:

AlgorithmSettings, SupervisedAlgorithmSettings

Method Summary

int	getMaximumNumberOfPredictors() Returns the maximum number of predictors.
OraABNModelType	getModelType() Returns the ABN model type enumeration.
int	getNaiveBayesNumberOfPredictors() Returns the number of predictors used in NB model.
void	setMaximumNumberOfPredictors(int maxPredictors) Sets the maximum number of predictors.
void	setModelType(OraABNModelType modelType) Sets the model type enumeration.
void	setNaiveBayesNumberOfPredictors(int nbPredictors) Sets the number of predictors in the NB model.

Methods inherited from interface javax.datamining.base.AlgorithmSettings

getMiningAlgorithm, verify

Method Detail

getModelType

public OraABNModelType getModelType()

Returns the ABN model type enumeration.

Returns:

ABNModelType

setModelType

public void setModelType(OraABNModelType modelType)

Sets the model type enumeration.

Parameters:

modelType -

Returns:

void

getNaiveBayesNumberOfPredictors

public int getNaiveBayesNumberOfPredictors()

Returns the number of predictors used in NB model.

Returns:

int

setNaiveBayesNumberOfPredictors

public void setNaiveBayesNumberOfPredictors(int nbPredictors)

Sets the number of predictors in the NB model.

Parameters:

nbPredictors -

Returns:

void

getMaximumNumberOfPredictors

public int getMaximumNumberOfPredictors()

Returns the maximum number of predictors.

Returns:

int

setMaximumNumberOfPredictors

public void setMaximumNumberOfPredictors(int maxPredictors)

Sets the maximum number of predictors.

Parameters:

maxPredictors -

Returns:

void