Serialized Form
m_count
int m_count
m_confidence
float m_confidence
m_target
Category m_target
m_targetItems
java.util.Vector m_targetItems
m_parentChildTableName
java.lang.String m_parentChildTableName
m_nodeTableName
java.lang.String m_nodeTableName
m_valueTableName
java.lang.String m_valueTableName
m_timingTableName
java.lang.String m_timingTableName
m_depth
int m_depth
m_numOfNetworkFeature
int m_numOfNetworkFeature
m_numOfConsecutivePrunedNF
int m_numOfConsecutivePrunedNF
m_buildTime
int m_buildTime
m_maxPredictors
int m_maxPredictors
m_NBNumPredictors
int m_NBNumPredictors
m_modelBuildType
ABNModelBuildType m_modelBuildType
m_destinationAttribute
Attribute m_destinationAttribute
- This indicates the column name to appear in the apply output table.
m_contentOption
ApplyResultContentOption m_contentOption
- Deprecated.
m_nPairs
int m_nPairs
m_useTop
boolean m_useTop
m_probabilityColumn
Attribute m_probabilityColumn
m_sourceAttribute
MiningAttribute m_sourceAttribute
m_targetValue
java.util.Vector m_targetValue
m_probabilityColumn
Attribute m_probabilityColumn
m_rankColumn
Attribute m_rankColumn
m_minimumSupport
float m_minimumSupport
- Specifies the minimum support value for the large itemsets (0..1]. Typically, this value is very small (e.g., 0.01)
m_minimumConfidence
float m_minimumConfidence
- Specifies the minimum confidence value for the rules (0..1]. Typically, this value is close to 1 (e.g., 0.9)
m_maximumRuleLength
int m_maximumRuleLength
- This specifies the maxinum length of the rules in terms of the number of items in the rules. This is used as a constraint to the function in order to finish the function quickly.
m_excludedCategory
java.util.Vector m_excludedCategory
- This is a list of categories that are not to be used for rule discovery. This is used as a constraint to the function in order to finish the function quickly. It is not used for ODM 1.
selectCategories
oracle.dmt.odm.settings.function.AssociationRulesFunctionSettings.select_categories selectCategories
m_numberOfTransactions
int m_numberOfTransactions
- The number of transactions from which the model was built.
m_maxNumberOfItemsPerTransaction
int m_maxNumberOfItemsPerTransaction
- The size of the largest transaction in terms of the number of items in it.
m_avgNumberOfItemsPerTransaction
float m_avgNumberOfItemsPerTransaction
- The average size of the transactions in terms of the number of items.
m_numberOfItems
int m_numberOfItems
- The total number of items that are present in the transaction from which the model was built.
m_numberOfRules
int m_numberOfRules
- The number of rules identified.
m_ruleTableName
java.lang.String m_ruleTableName
- The associated rules table name. Note that this table name
alone cannot locate the table. The table is always stored in conjunction
with the model.
m_antecedentTableName
java.lang.String m_antecedentTableName
- Represents the associated antecedent table name. Note that this table
name alone cannot locate the table. The table is always stored in conjunction
with the model.
m_items
java.util.Vector m_items
- A list of the items that were used for building the model.
m_name
java.lang.String m_name
m_dataType
DataType m_dataType
m_attribute
MiningAttribute m_attribute
m_displayName
java.util.Vector m_displayName
m_frequency
java.util.Vector m_frequency
m_numberOfBins
int m_numberOfBins
m_attributeImportanceEntry
java.util.Vector m_attributeImportanceEntry
m_tableName
java.lang.String m_tableName
m_value
java.lang.String m_value
m_displayName
java.lang.String m_displayName
- Display name of the Category
m_value
java.lang.String m_value
- Value of the Category
m_dataType
DataType m_dataType
- Data type of the Category
m_matrixVector
java.util.Vector m_matrixVector
- A vector that will be used to store a list of category matrix entry java objects.
m_diagonalDefault
float m_diagonalDefault
- Default values for diagonal elements of the matrix.
m_offDiagonalDefault
float m_offDiagonalDefault
- Default value for non-diagonal elements.
m_name
java.lang.String m_name
m_dataType
DataType m_dataType
m_listOfCategories
java.util.Vector m_listOfCategories
m_prior
PriorProbabilities m_prior
m_costMatrix
CategoryMatrix m_costMatrix
DM_SINGLE_VALUE
java.lang.String DM_SINGLE_VALUE
DM_MULTI_VALUE
java.lang.String DM_MULTI_VALUE
selectPrior
oracle.dmt.odm.settings.function.ClassificationFunctionSettings.select_prior selectPrior
m_id
float m_id
- test result id in EIS classification test result table
m_accuracy
float m_accuracy
- The percentage of correct classification
m_confusionMatrix
CategoryMatrix m_confusionMatrix
- This represents the confusion matrix for this test result. A confusion matrix is a matrix whose rows and columns are the target categories used to build the classifier. It is one of the factors to measure the goodness of them odel. Each entry in the matrix contains the value of classification results from the test data (i.e., the actual target versus the predicted target). The rows indicate the actual target categories, whereas the columns indicates the predicted (classified) target categories.
m_testResultName
java.lang.String m_testResultName
- This indicates the name of the test results.
m_clModel
ClusteringModel m_clModel
m_id
int m_id
m_recordCount
int m_recordCount
m_centroid
ClusterCentroid m_centroid
m_distribution
oracle.dmt.odm.model.ClusterDistribution m_distribution
m_level
int m_level
m_parent
Cluster m_parent
m_child
java.util.Vector m_child
m_splitPredicate
Predicate m_splitPredicate
m_entries
java.util.Vector m_entries
m_attribute
MiningAttribute m_attribute
m_value
Category m_value
m_maxNumberOfClusters
int m_maxNumberOfClusters
m_numberOfClusters
int m_numberOfClusters
m_numberOfLeaves
int m_numberOfLeaves
m_root
int m_root
m_numberOfLevels
int m_numberOfLevels
m_inputDataRecordCount
int m_inputDataRecordCount
m_priorTableName
java.lang.String m_priorTableName
m_condProbTableName
java.lang.String m_condProbTableName
m_rulesTableName
java.lang.String m_rulesTableName
m_clusterTableName
java.lang.String m_clusterTableName
m_maximumNetworkFeatureDepthArray
int[] m_maximumNetworkFeatureDepthArray
- Deprecated.
m_bBad
boolean m_bBad
- Deprecated.
m_sParams
java.lang.String m_sParams
- Deprecated.
selectSettingsArray
oracle.dmt.odm.settings.algorithm.CombinationAdaptiveBayesNetworkSettings.select_settings_array selectSettingsArray
- Deprecated.
m_singleThresholdArray
float[] m_singleThresholdArray
- Deprecated.
m_pairwiseThresholdArray
float[] m_pairwiseThresholdArray
- Deprecated.
m_combination_option
PairCombinationsOption m_combination_option
- Deprecated.
selectSettingsArray
oracle.dmt.odm.settings.algorithm.CombinationNaiveBayesSettings.select_settings_array selectSettingsArray
- Deprecated.
m_count
int m_count
m_probability
float m_probability
m_consequentMiningAttribute
MiningAttribute m_consequentMiningAttribute
m_antecedentMiningAttribute
java.util.Vector m_antecedentMiningAttribute
m_maValue
java.util.Hashtable m_maValue
m_crossValidateSettingsName
java.lang.String m_crossValidateSettingsName
- Cross-validate mining function settings
m_usage
AttributeUsage m_usage
m_attribute
MiningAttribute m_attribute
m_preparationStatus
DataPreparationStatus m_preparationStatus
m_usageEntries
java.util.Vector m_usageEntries
mName
java.lang.String mName
mBinningDetails
AttributeDiscretization mBinningDetails
value
java.lang.String value
ID
int ID
m_numberofFeatures
java.lang.Integer m_numberofFeatures
m_name
java.lang.String m_name
m_value
java.lang.String m_value
Iterations
int Iterations
Distance
DistanceFunction Distance
Error
float Error
StopCriterion
ClusteringStoppingCriterion StopCriterion
m_percentageOfRecordsCumulative
float m_percentageOfRecordsCumulative
- This indicates the percentage of the records up to this quantile.
m_liftQuantile
float m_liftQuantile
- This indicates the lift value of this quantile.
m_liftCumulative
float m_liftCumulative
- This indicates the cumulative lift value up to this quantile.
m_numberOfTargetsCumulative
int m_numberOfTargetsCumulative
- This indicates the cumulative number of targets up to this quantile.
m_numberOfNonTargetsCumulative
int m_numberOfNonTargetsCumulative
- This indicates the cumulative number of non-targets up to this quantile.
m_targetDensity
float m_targetDensity
- This indicates the percentage of target values in this quantile.
m_targetDensityCumulative
float m_targetDensityCumulative
- This indicates the percentage of cumulative target values up to this quantile.
m_percentageTargetCumulative
float m_percentageTargetCumulative
- This indicates the percentage target cumulative
- Since:
- 10.0.1
m_location
oracle.dmt.odm.Location m_location
m_columnName
java.lang.String m_columnName
m_ROWID
oracle.sql.ROWID m_ROWID
m_bytesROWID
byte[] m_bytesROWID
m_attributes
java.util.Vector m_attributes
m_cat_discretization_lad
LocationAccessData m_cat_discretization_lad
m_num_discretization_lad
LocationAccessData m_num_discretization_lad
m_algorithm
MiningAlgorithm m_algorithm
selectSettings
oracle.dmt.odm.settings.algorithm.MiningAlgorithmSettings.select_settings selectSettings
m_items
java.util.Vector m_items
- This contains an ordered list of apply content items.
m_maoName
java.lang.String m_maoName
m_maoId
int m_maoId
apply_content_settings
oracle.dmt.odm.result.MiningApplyOutput.select_apply_content_settings apply_content_settings
m_schemaName
java.lang.String m_schemaName
m_applyOutputTableName
java.lang.String m_applyOutputTableName
m_applyOutput
MiningApplyOutput m_applyOutput
m_applyOutputLoc
LocationAccessData m_applyOutputLoc
m_applyResultName
java.lang.String m_applyResultName
readObject
private void readObject(java.io.ObjectInputStream in)
throws java.io.IOException,
java.lang.ClassNotFoundException
m_attributeType
AttributeType m_attributeType
- This indicates the type of this mining attribute. One may argue that this must be specified in attribute usage because this is about how an attribute is used. Also, it is possible that an attribute may be both categorical and numerical in some rare cases. In ODM, however, we don't support this notion and hence this indicator may as well be here.
m_isKey
boolean m_isKey
m_nestedAttributes
java.util.Vector m_nestedAttributes
m_isParentGroup
boolean m_isParentGroup
m_isNested
boolean m_isNested
m_valueCount
int m_valueCount
m_categorySet
CategorySet m_categorySet
m_sparsitySpecification
SparsitySpecification m_sparsitySpecification
selmodel
oracle.dmt.odm.result.MiningBuildResult.select_model_data selmodel
selmfs
oracle.dmt.odm.result.MiningBuildResult.select_mfs_name selmfs
m_functionSettingsName
java.lang.String m_functionSettingsName
m_algorithmName
java.lang.String m_algorithmName
m_settingsName
java.lang.String m_settingsName
m_resultModelName
java.lang.String m_resultModelName
m_taskInputData
PhysicalDataSpecification m_taskInputData
m_inputModelName
java.lang.String m_inputModelName
- This specifies the name of the input mining model
readObject
private void readObject(java.io.ObjectInputStream in)
throws java.io.IOException,
java.lang.ClassNotFoundException
- This method is invoked when an MFS is restored. This method converts 9.0.1 MFS object to 9.2.0 compatible one.
validateBeforeStore
boolean validateBeforeStore
m_name
java.lang.String m_name
- This identifies the name of this
MiningFunctionSettings object.
m_miningFunction
MiningFunction m_miningFunction
- This identifies the mining function to be performed. ODM supports only three functions: association rules, classification and regression.
m_algorithmSettings
MiningAlgorithmSettings m_algorithmSettings
- This refers to the mining algorithms object that specifies the detailed parameters of the function. If omitted, the underlying mining data system selects a mining algorithm based on the other parameters specified in the mining function settings object.
m_usageSpecification
DataUsageSpecification m_usageSpecification
- This refers to an attribute usage specification object that describes how each mining attribute is to be interpreted and used.
m_logicalDataSpec
LogicalDataSpecification m_logicalDataSpec
- This refers to a mining data specification object that contains the mining attributes to be used for the specified mining function. The user must provide a LDS when creating a MFS object.
m_algorithmName
java.lang.String m_algorithmName
selectSettings
oracle.dmt.odm.settings.function.MiningFunctionSettings.select_settings selectSettings
liftResultElement
java.util.Vector liftResultElement
- This contains the list of the lift elements.
m_TotalTargetCount
int m_TotalTargetCount
m_TotalTotalCount
int m_TotalTotalCount
lift_result_entry
oracle.dmt.odm.result.MiningLiftResult.select_lift_result_entry lift_result_entry
m_numberOfQuantiles
int m_numberOfQuantiles
- Number of quantiles
m_positiveTargetValue
Category m_positiveTargetValue
- Specifies the positive target value to be used for compute lift.
m_liftResultName
java.lang.String m_liftResultName
- Name of the lift computation results
function
MiningFunction function
algortihm
MiningAlgorithm algortihm
- Indicates the mining algorithm used to create the model.
settings
MiningFunctionSettings settings
- Indicates the mining function settings used to build the model. The mining function settings can be persistent by itself (for phase II).
BinNumericTableName
java.lang.String BinNumericTableName
BinCategoricalTableName
java.lang.String BinCategoricalTableName
modelName
java.lang.String modelName
m_modelSignature
ModelSignature m_modelSignature
readObject
private void readObject(java.io.ObjectInputStream in)
throws java.io.IOException,
java.lang.ClassNotFoundException
VARRAY_MAX_SIZE
int VARRAY_MAX_SIZE
className
java.lang.Class className
m_tImmutazingThread
java.lang.Thread m_tImmutazingThread
- Synchronization functions and variables fro immutability are below
m_nBusyCount
int m_nBusyCount
m_name
java.lang.String m_name
- The name of the result in the context of where it is persisted. In other words, the name alone cannot be used to locate the result.
m_startingTimestamp
java.sql.Timestamp m_startingTimestamp
- This indicates the time when the result was started.
m_completionTimestamp
java.sql.Timestamp m_completionTimestamp
- This indicates the time when the result was completed.
m_inputMiningData
oracle.dmt.odm.Location m_inputMiningData
- This indicates the location of the mining data from which the result was generated.
m_miningModel
java.lang.String m_miningModel
- This indicates the name of the mining model in ODM schema, ODM_MINGING_MODEL from which the result was generated.
m_modelID
int m_modelID
mining_result
oracle.dmt.odm.result.MiningResult.select_mining_result mining_result
location_access_data
oracle.dmt.odm.result.MiningResult.select_location_access_data location_access_data
result_property
oracle.dmt.odm.result.MiningResult.select_result_property result_property
m_ruleId
int m_ruleId
m_support
float m_support
m_antecedent
RuleComponent m_antecedent
m_consequent
RuleComponent m_consequent
m_annotation
java.util.Vector m_annotation
m_supportCount
int m_supportCount
m_taskName
java.lang.String m_taskName
m_taskType
java.lang.String m_taskType
m_taskId
int m_taskId
m_nullCount
int m_nullCount
m_percentageMissingTargets
float m_percentageMissingTargets
m_percentageMissingPredictors
float m_percentageMissingPredictors
m_exportModelLocation
LocationCellAccessData m_exportModelLocation
m_miningStandardType
MiningStandardType m_miningStandardType
m_inputModelName
java.lang.String m_inputModelName
m_importModelLocation
LocationCellAccessData m_importModelLocation
m_miningStandardType
MiningStandardType m_miningStandardType
m_outputModelName
java.lang.String m_outputModelName
m_masArray
MiningAlgorithmSettings[] m_masArray
- Deprecated.
selectNestedSettings
oracle.dmt.odm.settings.algorithm.ModelSeekerClassificationAlgorithmSettings.select_nested_settings selectNestedSettings
- Deprecated.
m_msResultID
long m_msResultID
- Deprecated.
m_msResultEntries
ModelSeekerResultEntry[] m_msResultEntries
- Deprecated.
m_indxBestModel
int m_indxBestModel
- Deprecated.
m_locTestData
java.lang.String m_locTestData
- Deprecated.
m_settingName
java.lang.String m_settingName
- Deprecated.
modelseeker_result_entry
oracle.dmt.odm.result.ModelSeekerResult.select_modelseeker_result_entry modelseeker_result_entry
- Deprecated.
modelseeker_result_entryWIA
oracle.dmt.odm.result.ModelSeekerResult.select_modelseeker_result_entryWIA modelseeker_result_entryWIA
- Deprecated.
modelseeker_result
oracle.dmt.odm.result.ModelSeekerResult.select_modelseeker_result modelseeker_result
- Deprecated.
m_modelName
java.lang.String m_modelName
- Deprecated.
m_algorithmType
MiningAlgorithm m_algorithmType
- Deprecated.
m_buildDuration
long m_buildDuration
- Deprecated.
m_testResultName
java.lang.String m_testResultName
- Deprecated.
m_liftResultName
java.lang.String m_liftResultName
- Deprecated.
m_CFSName
java.lang.String m_CFSName
- Deprecated.
m_figureOfMerit
float m_figureOfMerit
- Deprecated.
m_resultName
java.lang.String m_resultName
- Deprecated.
m_prefix
java.lang.String m_prefix
- Deprecated.
m_testLiftPDS
PhysicalDataSpecification m_testLiftPDS
- Deprecated.
m_numberOfQuantilesForLift
int m_numberOfQuantilesForLift
- Deprecated.
m_positiveTargetValue
Category m_positiveTargetValue
- Deprecated.
m_weight
float m_weight
- Deprecated.
m_numberOfKeptModels
java.lang.Integer m_numberOfKeptModels
- Deprecated.
m_bBad
boolean m_bBad
- Deprecated.
m_sParams
java.lang.String m_sParams
- Deprecated.
m_featureNum
int m_featureNum
- Deprecated.
m_depth
int m_depth
- Deprecated.
m_segmentBuildTime
int m_segmentBuildTime
- Deprecated.
m_featureScoringTime
int m_featureScoringTime
- Deprecated.
m_estFeatureScoringTime
int m_estFeatureScoringTime
- Deprecated.
m_isTerminated
boolean m_isTerminated
- Deprecated.
m_isAccepted
boolean m_isAccepted
- Deprecated.
m_singletonThreshold
float m_singletonThreshold
m_pairwiseThreshold
float m_pairwiseThreshold
m_condProbExpr
java.util.Vector m_condProbExpr
m_maxNumberOfIterations
int m_maxNumberOfIterations
m_minConvergenceTolerance
float m_minConvergenceTolerance
m_randomSeedSetting
int m_randomSeedSetting
m_numIterations
int m_numIterations
m_error
float m_error
m_TransformedMapTableName
java.lang.String m_TransformedMapTableName
m_TextMiningXformTableName
java.lang.String m_TextMiningXformTableName
m_EncodedFeaturesTable
java.lang.String m_EncodedFeaturesTable
m_seqAttribute
Attribute m_seqAttribute
m_sensitivity
float m_sensitivity
m_errorCode
int m_errorCode
m_parameters
java.lang.Object[] m_parameters
format
DataFormatType format
ladLocAccessData
LocationAccessData ladLocAccessData
m_pdsName
java.lang.String m_pdsName
m_pdsId
int m_pdsId
m_priorVector
java.util.Vector m_priorVector
m_values
java.util.Vector m_values
m_pred
AttributeInstance m_pred
m_prob
AttributeInstance m_prob
selectSettings
oracle.dmt.odm.settings.function.RegressionFunctionSettings.select_settings selectSettings
m_errorMetric
ErrorMetric m_errorMetric
m_id
float m_id
- test result id in EIS Regression test result table
m_rootMeanSquareError
float m_rootMeanSquareError
- The root mean square error
m_testResultName
java.lang.String m_testResultName
- This indicates the name of the test results.
m_type
RuleAnnotationType m_type
m_value
java.lang.String m_value
m_attributeType
AttributeType m_attributeType
m_desiredAccuracy
float m_desiredAccuracy
- This specifies the desired accuracy of the resulting model. It is not mandatopry, and the data mining system does its best to achieve this level of accuracy whenever possible.
m_multipleTargetValuePerCase
boolean m_multipleTargetValuePerCase
- This specifies the way to handle target value per case, it will handle single target value per case if the boolean value is set to false. Otherwise, it will handle multiple target value per case if the the boolean value is set to true. The default boolean value is false.
m_targetValueCount
int m_targetValueCount
- Deprecated. Replaced with
m_numberOfPriors.
- The number of distinct values in the target attribute
m_conditionsTableName
java.lang.String m_conditionsTableName
- conditions table
m_categorySetID
java.lang.Integer m_categorySetID
- Category Set ID
m_priorsTableName
java.lang.String m_priorsTableName
- priors table
m_costMatrixTableName
java.lang.String m_costMatrixTableName
m_numberOfConditions
int m_numberOfConditions
m_numberOfPriors
int m_numberOfPriors
m_supportVectorCount
int m_supportVectorCount
- Default value of count of Support Vectors resulting from the model build is 0.
m_normalizationTableName
java.lang.String m_normalizationTableName
m_transformatedMapTableName
java.lang.String m_transformatedMapTableName
m_textMiningXformTableName
java.lang.String m_textMiningXformTableName
m_normalization
Normalization m_normalization
- Default value of normalization is minMax.
m_kernelFunction
KernelFunction m_kernelFunction
- Default value of kernel function is linear.
m_tolerance
float m_tolerance
- Default value of tolerance is 0.001;.
m_standardDeviation
java.lang.Float m_standardDeviation
- Default value of the standard deviation of the Gaussian kernel is null. The value will be computed if default value is null.
m_complexityFactor
java.lang.Float m_complexityFactor
- Default value of the parameter trading off complexity for prediction loss is null. The value will be computed if default value is null.
m_kernelCacheSize
int m_kernelCacheSize
- Default value of the kernel function cache size is 50000000.
m_epsilon
java.lang.Float m_epsilon
- Default value of the width of the allowed error in epsilon-insensitive regression is 0.1.
m_sequenceIdAttribute
Attribute m_sequenceIdAttribute
- Identifies the mining attribute to be used as transaction ID.
m_attributeIdAttribute
Attribute m_attributeIdAttribute
- Points to the mining attribute that represents attribute ID of each transaction. When we populate attribute usage entries off the discretization tables, this attribute is used to create mining attributes that are values of this column.
m_valueIdAttribute
Attribute m_valueIdAttribute
- Identifies the mining attribute that represents the value of each transaction (optional).
m_groupIdIdAttribute
Attribute m_groupIdIdAttribute
- If lack of domain ID causes TNB a problem, throw an exception.
INT_DATATYPE
java.lang.String INT_DATATYPE
STRING_DATATYPE
java.lang.String STRING_DATATYPE
FLOAT_DATATYPE
java.lang.String FLOAT_DATATYPE