Package oracle.dmt.odm.settings.algorithm

This package contains Java classes representing mining algorithm settings.

See:
Description

Class Summary

AdaptiveBayesNetworkSettings	An instance of AdaptiveBayesNetworkSettings is used to specify settings for the Adaptive Bayes Network algorithm.
AprioriAlgorithmSettings	An instance of AprioriAlgorithmSettings is used to specify settings for the Apriori 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	Deprecated. Model Seeker functionality is deprecated in version 10.1.
CombinationModelSettings	Deprecated. Model Seeker functionality is deprecated in version 10.1.
CombinationNaiveBayesSettings	Deprecated. Model Seeker functionality is deprecated in version 10.1.
FeatureExtractionAlgorithmSettings	An instance of FeatureExtractionAlgorithmSettings is used to specify optional parameters common to feature extraction algorithm.
KMeansAlgorithmSettings	An instance of KMeansAlgorithmSettings is used to specify settings for the KMeans clustering algorithm.
MinimumDescriptionLengthSettings	An instance of MinimumDescriptionLengthSettings is used to specify parameters for the Minimum Description Length algorithm supporting attribute importance.
MiningAlgorithmSettings	The abstract class MiningAlgorithmSettings is the common superclass of all mining algorithm settings.
ModelSeekerClassificationAlgorithmSettings	Deprecated. Model Seeker functionality is deprecated in version 10.1.
NaiveBayesSettings	An instance of NaiveBayesSettings is used to specify settings for the Naive Bayes algorithm.
NMFAlgorithmSettings	An instance of NMFAlgorithmSettings is used to specify settings for the NMF Feature Extraction algorithm.
OClusterAlgorithmSettings	An instance of OClusterAlgorithmSettings holds metadata about settings that are required in the O-Cluster algorithm.
PredictorVarianceSettings	Deprecated. As of 10.1.0.
SupportVectorMachineSettings	The abstract class SupportVectorMachineSettings is the common superclass of all Support Vector Machine (SVM) mining algorithm settings.
SVMClassificationSettings	An instance of SVMClassificationSettings is used to specify settings for the Support Vector Machine (SVM) mining algorithm to build a classification mining model.
SVMRegressionSettings	An instance of SVMRegressionSettings is used to specify settings for the Support Vector Machine (SVM) mining algorithm to build a regression mining model.

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:

• AdaptiveBayesNetworkSettings: used in conjunction with ClassificationFunctionSettings to build a AdaptiveBayesNetworkModel
• AttributeImportanceAlgorithmSettings: An abstract class for all attribute importance settings.
  • PredictorVarianceSettings: used in conjunction with AttributeImportanceFunctionSettings to build a AttributeImportanceModel
• NaiveBayesSettings: used in conjunction with ClassificationFunctionSettings to build a NaiveBayesModel
• ClusteringAlgorithmSettings: An abstract class for all clustering algorithm settings.
  • KMeansAlgorithmSettings: k-means clustering algorithm
  • OClusteringAlgorithmSettings: A proprietary clsutering algorithm of Oracle Data Mining
• SupportVectorMachineSettings: An abstract class for all SVM algorithm settings.
  • SVMClassificationSettings: classification
  • SVMRegressionSettings: approximation/regression
• FeatureExtractionAlgorithmSettings: An abstract class for all feature extraction algorithm settings.
  • NMFAlgorithmSettings: used to specify settings for the NMF Feature Extraction algorithm
• Algorithm settings for model seeker task: Oracle Model Seeker builds a set of classification models of one type (either NaiveBayesModel or AdaptiveBayesNetworkModel)
  • CombinationalAlgorithmSettings: An abstract class that contains a compact representation of combinations of parameters for a specific algorithm settings.
    • CombinationalAdaptiveBayesNetworkSettings: Used to build a set of AdaptiveBayesNetworkModel via model seeker task.
    • CombinationalNaiveBayesSettings: Used to build a set of NaiveBayesModel via model seeker task.
  • ModelSeekerClassificationAlgorithmSettings: A container class for multiple instances of classification algorithm settings of one kind. It may contain either NaiveBayesSettings or AdaptiveBayesNetworkSettings.