Package oracle.dmt.odm.settings.algorithm

This package contains Java classes representing mining algorithm settings.

See:
          Description

Class Summary
ClassDescription
AdaptiveBayesNetworkSettings An instance of AdaptiveBayesNetworkSettings is used to specify settings for the Adaptive Bayes Network algorithm.
AttributeImportanceAlgorithmSettings The abstract class AttributeImportanceAlgorithmSettings is the common superclass of all attribute importance algorithms and is used to specify parameters specific to Attribute Importance algorithms.
ClusteringAlgorithmSettings An instance of ClusteringAlgorithmSettings is used to specify optional parameters common to clustering algorithm.
CombinationAdaptiveBayesNetworkSettings An instance of CombinationAdaptiveBayesNetworkSettings is used to specify multiple settings for the Adaptive Bayes Network algorithm to be used by Model Seeker.
CombinationModelSettings The abstract class CombinationModelSettings is the common super class for the algorithm settings that specify model combinations of a single type.
The following sub-classes of CombinationModelSettings are supported:
CombinationNaiveBayesSettings and
CombinationAdaptiveBayesNetworkSettings.
CombinationNaiveBayesSettings An instance of CombinationNaiveBayesSettings is used to specify multiple settings for the Naive Bayes algorithm to be used by Model Seeker.
KMeansAlgorithmSettings An instance of KMeansAlgorithmSettings is used to specify settings for the KMeans clustering algorithm.
MiningAlgorithmSettings The abstract class MiningAlgorithmSettings is the common superclass of all mining algorithm settings.
ModelSeekerClassificationAlgorithmSettings An instance of ModelSeekerClassificationAlgorithmSettings is used to specify multiple algorithm settings to be used by Model Seeker.
NaiveBayesSettings An instance of NaiveBayesSettings is used to specify settings for the Naive Bayes algorithm.
OClusterAlgorithmSettings An instance of OClusterAlgorithmSettings holds metadata about settings that are required in the O-Cluster algorithm.
PredictorVarianceSettings An instance of PredictorVarianceSettings is used to specify parameters for the Predictor Variance algorithm supporting attribute importance.
 

Package oracle.dmt.odm.settings.algorithm Description

This package contains Java classes representing mining algorithm settings. An algorithm settings object captures the parameters associated with a particular algorithm. It allows a knowledgeable user to fine tune algorithm parameters. Generally, not all parameters must be specified, however, those specified are taken into account by the DMS. Separating algorithm settings from function settings provides a natural and convenient separation for those users experienced with data mining and those only familiar with mining functions.

ODM supports the following types of algorithm settings: