Class Summary |
Apriori |
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AssignAverageValue |
This operator takes the average of the values in the column that
has missing values, and replaces missing values with this average.
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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. |
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. |
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.
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DateToNumeric |
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DeleteRecordsWithMissingValues |
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Discretization |
The class Discretization is abstract class
for the operators of type Discretization |
EvaluateAdvantageOfTFIDFTransformation |
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EvaluateResults |
This class is the superclass for evaluation operators. |
ExecutableOperator |
Abstract superclass of all executable operators in
MiningMart. |
ExponentialMovingFunction |
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FeatureConstruction |
This class is the superclass for all operators whose output
is a BaseAttribute. |
FeatureConstructionWithTFIDF |
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FeatureSelection |
This class is the super class for all Feature Selection operators.
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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.
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LinearScaling |
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LogScaling |
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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 |
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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).
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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 |
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NumericalIntervalManualDiscretization |
The class NumericalIntervalManualDiscretization implements method
generateSQL creating virtual column definition for discretization of
numerical intervals according to given discretization specification.
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PartialMapping |
The class PartialMapping maps values
for which no mapping has been specified into a target attribute value.
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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.
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RemoveDuplicates |
Creates a view on the input table/view that contains
no two equal tuples (rows). |
Repeat |
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ReversePivotize |
This operator denormalizes or flattens out certain attributes, which is called
Pivotizing. |
RowSelection |
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RowSelectionByDeleteMissingValues |
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RowSelectionByQuery |
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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 |
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Scaling |
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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 |
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SimpleMovingFunction |
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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.
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TimeOperator |
Abstract super class for all time operators creating a
new table by calling a stored procedure of the
database. |
TupleWiseModelApplier |
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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 Columnset s for a single Concept .
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WeightedMovingFunction |
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Windowing |
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YaleModelApplier |
This operator applies a model written by YALE to a set of examples.
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