Package edu.udo.cs.miningmart.operator

Interface Summary

AttrDerivInterface

Interface to be implemented by any class that provides a method for the MiningMart operator AttributeDerivation.

Class Summary

Apriori
AssignAverageValue	This operator takes the average of the values in the column that has missing values, and replaces missing values with this average.
AssignDefault	This operator replaces the missing values with a default value which is specified with the parameter DefaultValue.
AssignMedianValue	This operator replaces missing values by the median value of the column.
AssignModalValue	This operator replaces missing values with the modal value of that column.
AssignStochasticValue	This operator uses statistical information about the distribution of the values in the target attribute to randomly choose replacements for the missing values such that the distribution is not expected to change.
AttributeDerivation	An operator that uses a Java method programmed by the user to create values of the OutputAttribute.
Binarify	This operator creates new binary attributes that realise a boolean flag indicating for each value of the target attribute whether it occurs in that row/entity.
ComputeSVMError	This class computes an error for the SupportVectorMachine.
ConceptOperator	This abstract class is the superclass for all operators whose output is a concept.
CreateManyToManyRelation
CreateOneToManyRelation
CreatePrimaryKey	This operator is able to convert a view with no key and maybe multiple occurences of tuples into a view with a single primary key attribute.
DateToNumeric
DeleteRecordsWithMissingValues
Discretization	The class Discretization is abstract class for the operators of type Discretization
EvaluateAdvantageOfTFIDFTransformation
EvaluateResults	This class is the superclass for evaluation operators.
ExecutableOperator	Abstract superclass of all executable operators in MiningMart.
ExponentialMovingFunction
FeatureConstruction	This class is the superclass for all operators whose output is a BaseAttribute.
FeatureConstructionByRelation
FeatureConstructionWithTFIDF
FeatureSelection	This class is the super class for all Feature Selection operators.
FeatureSelectionByAttributes	This operator chooses all Features that are present in TheOutputConcept.
FeatureSelectionWithSVM	This operator uses the SVM algorithm mySVM/db, which estimates the generalisation performance of an SVM on different feature subsets, to choose the best feature subset.
GenericFeatureConstruction	This operator constructs a new feature by using SQL code (provided by the parameter sql_string) for the column definition for the new feature.
JoinByKey	This operator joins several concepts using their specified keys.
LinearScaling
LogScaling
ManualDiscretization	The class ManualDiscretization is abstract class for the operators of type ManualDiscretization
Mapping	The class Mapping is abstract class for the operators of type Mapping
MappingWithDefaultValue	The class MappingWithDefaultValue maps values for which no mapping has been specified into a constant value It implements abstract method getDefault declared in Mapping.
Materialize
MaterializeRelation
MaterializeWithPKs
MergeAttributes	This operator merges two attributes.
MissingValues	The abstract superclass of all operators that replace a missing value with a new value.
MissingValuesWithRegressionSVM	The class MissingValuesWithRegressionSVM implements the abstract methods createFunction and defineOutputDatatype (from class AttributeOperator).
ModelApplier	This class is the abstract super-class for model-applying operators.
MultipleCSOperator	This abstract class is the superclass for all operators that create more than one ColumnSet for the output concept.
MultiRelationalFeatureConstruction
NumericalIntervalManualDiscretization	The class NumericalIntervalManualDiscretization implements method generateSQL creating virtual column definition for discretization of numerical intervals according to given discretization specification.
PartialMapping	The class PartialMapping maps values for which no mapping has been specified into a target attribute value.
Pivotize	This operator denormalizes or flattens out certain attributes, which is called Pivotizing.
PrepareForYale	This operator creates a YALE experiment file (XML) to ease the combination of MiningMart preprocessing and YALE learning.
RemoveDuplicates	Creates a view on the input table/view that contains no two equal tuples (rows).
RemoveFeatures	This operator chooses all Features that are present in TheOutputConcept.
Repeat
ReverseFeatureConstruction
ReversePivotize	This operator folds some given attributes into one, which is called Reverse Pivotizing.
RowSelection
RowSelectionByDeleteMissingValues
RowSelectionByQuery
RowSelectionByRandomSampling	This operator randomly selects rows with a probability that is computed such that roughly as many rows are selected as are given in the parameter HowMany.
RowSelectionByUnbiasing
Scaling
Segmentation	This is the abstract super class for all Segmentation operators.
SegmentationByPartitioning	This operator segments an input concept randomly.
SegmentationStratified	This operator segments an input concept according to the different values of a specified attribute, such that each segment contains the rows where this attribute has the same value.
SignalToSymbolProcessing
SimpleMovingFunction
SingleCSOperator	This abstract class is the superclass for all operators that create a single ColumnSet for the output concept.
SpecifiedStatistics	Creates a table in the business data schema with the statistics values in them.
SupportVectorMachineForClassification	This operator uses mySVM to realize a Support Vector Machine for classification.
SupportVectorMachineForRegression	This operator uses mySVM to realize a Support Vector Machine for regression.
SVMforDataMining	Abstract superclass for the two operators SupportVectorMachineForClassification and SupportVectorMachineForRegression
TimeIntervalManualDiscretization	The class TimeIntervalManualDiscretization implements method generateSQL creating virtual column definition for discretization of numerical intervals according to given discretization specification.
TimeOperator	Abstract super class for all time operators creating a new table by calling a stored procedure of the database.
TupleWiseModelApplier
Union	This operator provides a UNION of Concepts as part of SQL at the relational level.
UnionByKey	UnionByKey operator takes as an input concepts and selected features from these conpcepts.
Unsegment	This class realizes an operator for grouping segments of a Concept together.Applications of the operator SegmetationStratified usually result in several Columnsets for a single Concept.
WeightedMovingFunction
Windowing	Neue Version des Windowing-Operators ohne Stored Procedure.
WindowingOld
YaleModelApplier	This operator applies a model written by YALE to a set of examples.