Uses of Interface
com.rapidminer.example.Attribute

Packages that use Attribute

com.rapidminer.datatable	DataTables are the most important data container interface for RapidMiner which are used for all statistics and plotting purposes.
com.rapidminer.example	The data core classes of RapidMiner.
com.rapidminer.example.set	The available views (example sets) on the example tables.
com.rapidminer.example.table	The available example table implementations (data sources).
com.rapidminer.example.test	Test classes for classes in the example package.
com.rapidminer.generator	Provides feature generators.
com.rapidminer.operator	Provides operators for machine learning and data pre-processing.
com.rapidminer.operator.clustering	The base classes for clustering.
com.rapidminer.operator.features.aggregation	Provides operators for automatic feature aggregation.
com.rapidminer.operator.features.construction	Provides operators for automatic feature construction.
com.rapidminer.operator.generator	Provides operators for data generation.
com.rapidminer.operator.io	Operators to read data from files or write them into files.
com.rapidminer.operator.learner	Provides learning operators.
com.rapidminer.operator.learner.associations	This package contains classes and operators for association rule mining and frequent item set mining.
com.rapidminer.operator.learner.bayes	This package contains classes and operators for Naive Bayes learning.
com.rapidminer.operator.learner.functions	This package contains learners based on the concept of function approximation.
com.rapidminer.operator.learner.functions.kernel	Learning schemes which make use of kernel functions to transform the feature space, e.g. support vector machines.
com.rapidminer.operator.learner.functions.kernel.evosvm	Implementations of SVMs which makes use of general purpose optimization methods, e.g. evolutionary strategies or particle swarm optimization.
com.rapidminer.operator.learner.functions.kernel.hyperhyper	This package contains classes for the HyperHyper learner.
com.rapidminer.operator.learner.functions.kernel.jmysvm.examples	The package for data handling of the Java version of the support vector machine mySVM.
com.rapidminer.operator.learner.functions.neuralnet	This package contains a neural net learner based on Joone.
com.rapidminer.operator.learner.igss.hypothesis	Provides the hypothesis classes for learning operator Iterating Generic Sequential Sampling.
com.rapidminer.operator.learner.lazy	Learning schemes which perform lazy learning.
com.rapidminer.operator.learner.meta	Meta learning schemes which uses other learning operators to increase the performance.
com.rapidminer.operator.learner.rules	Provides rule learners.
com.rapidminer.operator.learner.subgroups.hypothesis	Provides helper classes for a subgroups discovery algorithm.
com.rapidminer.operator.learner.tree	Provides decision tree learners.
com.rapidminer.operator.learner.weka	Operators which encapsulate the learning schemes provided by Weka.
com.rapidminer.operator.performance	Provides performance evaluating operators and performance criteria.
com.rapidminer.operator.performance.cost	This package contains cost-based performance evaluations.
com.rapidminer.operator.postprocessing	Operators for post processing, usually used for models.
com.rapidminer.operator.preprocessing.discretization	Contains discretization operators which can be used to transform numerical into nominal attributes.
com.rapidminer.operator.preprocessing.filter	Containing filter operators changing the input example set, e.g. by removing certain attributes or changing the data.
com.rapidminer.operator.preprocessing.filter.attributes	This package contains the attribute filter.
com.rapidminer.operator.preprocessing.join	This package contains the operators for joining and merging example sets.
com.rapidminer.operator.preprocessing.normalization	Preprocessing operators used for normalization.
com.rapidminer.operator.preprocessing.series	Containing preprocessing operators for (time) series handling.
com.rapidminer.operator.visualization	The operators in this package are used for visualization purposes.
com.rapidminer.operator.visualization.dependencies	The operators in this package are used for the calculation and the visualization of dependency matrices like those for correlations etc.
com.rapidminer.tools.att	Provides tools for parsing the attribute description file.
com.rapidminer.tools.jdbc	Provides tools for database access via JDBC connections.
com.rapidminer.tools.math	Several tool classes for mathematical operations.
com.rapidminer.tools.math.function.aggregation	The classes in this package represent basic functions which can, for example, be used as aggregation functions.

Uses of Attribute in com.rapidminer.datatable

Constructors in com.rapidminer.datatable with parameters of type Attribute

Example2DataTableRowIterator(java.util.Iterator<Example> reader, java.util.List<Attribute> allAttributes, Attribute idAttribute)
Creates a new DataTable iterator backed up by examples.

Example2DataTableRowWrapper(Example example, java.util.List<Attribute> allAttributes, Attribute idAttribute)
Creates a new wrapper.

Constructor parameters in com.rapidminer.datatable with type arguments of type Attribute

Example2DataTableRowIterator(java.util.Iterator<Example> reader, java.util.List<Attribute> allAttributes, Attribute idAttribute)
Creates a new DataTable iterator backed up by examples.

Example2DataTableRowWrapper(Example example, java.util.List<Attribute> allAttributes, Attribute idAttribute)
Creates a new wrapper.

Uses of Attribute in com.rapidminer.example

Methods in com.rapidminer.example that return Attribute

Attribute[]	Attributes.createRegularAttributeArray() This method creates an attribute array from all regular attributes.
Attribute[]	AbstractAttributes.createRegularAttributeArray()
static Attribute[]	Tools.createRegularAttributeArray(ExampleSet exampleSet)
static Attribute	Tools.createSpecialAttribute(ExampleSet exampleSet, java.lang.String name, int valueType)
static Attribute	Tools.createWeightAttribute(ExampleSet exampleSet)
Attribute	AttributeParser.generateAttribute(LoggingHandler logging, java.lang.String constructionDescription, ExampleTable table)
Attribute	Attributes.get(java.lang.String name) Returns the attribute for the given name.
Attribute	AbstractAttributes.get(java.lang.String name)
Attribute	AttributeRole.getAttribute()
Attribute	Attributes.getCluster() Returns the cluster attribute or null if no label attribute is defined.
Attribute	AbstractAttributes.getCluster()
Attribute	Attributes.getCost() Returns the cost attribute or null if no label attribute is defined.
Attribute	AbstractAttributes.getCost()
Attribute	Attributes.getId() Returns the id attribute or null if no label attribute is defined.
Attribute	AbstractAttributes.getId()
Attribute	Attributes.getLabel() Returns the label attribute or null if no label attribute is defined.
Attribute	AbstractAttributes.getLabel()
Attribute	Attributes.getOutlier() Returns the outlier attribute or null if no label attribute is defined.
Attribute	AbstractAttributes.getOutlier()
Attribute	Attributes.getPredictedLabel() Returns the predicted label attribute or null if no label attribute is defined.
Attribute	AbstractAttributes.getPredictedLabel()
static Attribute[]	Tools.getRandomCompatibleAttributes(ExampleSet exampleSet, FeatureGenerator generator, java.lang.String[] functions, java.util.Random random)
Attribute	Attributes.getRegular(java.lang.String name) Returns the regular attribute for the given name.
Attribute	AbstractAttributes.getRegular(java.lang.String name)
Attribute	Attributes.getSpecial(java.lang.String name) Returns the special attribute for the given special name.
Attribute	AbstractAttributes.getSpecial(java.lang.String name)
Attribute	Attributes.getWeight() Returns the weight attribute or null if no label attribute is defined.
Attribute	AbstractAttributes.getWeight()
static Attribute[]	Tools.getWeightedCompatibleAttributes(AttributeWeightedExampleSet exampleSet, FeatureGenerator generator, java.lang.String[] functions, RandomGenerator random)
Attribute	AttributeIterator.next()
Attribute	Attributes.replace(Attribute first, Attribute second) Replaces the first attribute by the second.
Attribute	AbstractAttributes.replace(Attribute first, Attribute second)
static Attribute	Tools.selectAttribute(Attribute[] attributes, double[] probs, java.util.Random random)

Methods in com.rapidminer.example that return types with arguments of type Attribute

java.util.Iterator<Attribute>	Attributes.allAttributes() Returns an iterator over all attributes, including the special attributes.
java.util.Iterator<Attribute>	AbstractAttributes.allAttributes()
java.util.Iterator<Attribute>	Attributes.iterator() Iterates over all regular attributes.
java.util.Iterator<Attribute>	AbstractAttributes.iterator()

Methods in com.rapidminer.example with parameters of type Attribute

void	Attributes.addRegular(Attribute attribute) Adds the given attribute as regular attribute.
void	AbstractAttributes.addRegular(Attribute attribute)
static boolean	Tools.compatible(Attribute first, Attribute second) Returns true if value and block types of the first attribute are subtypes of value and block type of the second.
boolean	Attributes.contains(Attribute attribute) Returns true if this attribute set contains the given attribute.
boolean	AbstractAttributes.contains(Attribute attribute)
boolean	Example.equalValue(Attribute first, Attribute second) Returns true if both nominal values are the same (if both attributes are nominal) or if both real values are the same (if both attributes are real values) or false otherwise.
java.util.Date	Example.getDateValue(Attribute a) Returns the date value for the given attribute.
static double[]	Tools.getInverseProbabilitiesFromWeights(Attribute[] attributes, AttributeWeightedExampleSet exampleSet)
java.lang.String	Example.getNominalValue(Attribute a) Returns the nominal value for the given attribute.
double	Example.getNumericalValue(Attribute a) Returns the numerical value for the given attribute.
static double[]	Tools.getProbabilitiesFromWeights(Attribute[] attributes, AttributeWeightedExampleSet exampleSet)
static double[]	Tools.getProbabilitiesFromWeights(Attribute[] attributes, AttributeWeightedExampleSet exampleSet, boolean inverse) Calculates probabilities for attribute selection purposes based on the given weight.
AttributeRole	Attributes.getRole(Attribute attribute) Returns the attribute role for the given attribute.
AttributeRole	AbstractAttributes.getRole(Attribute attribute)
double	ExampleSet.getStatistics(Attribute attribute, java.lang.String statisticsName) Returns the desired statistic for the given attribute.
double	WeightedNumericalStatistics.getStatistics(Attribute attribute, java.lang.String name, java.lang.String parameter)
double	UnknownStatistics.getStatistics(Attribute attribute, java.lang.String statisticsName, java.lang.String parameter)
double	Statistics.getStatistics(Attribute attribute, java.lang.String statisticsName, java.lang.String parameter)
double	NumericalStatistics.getStatistics(Attribute attribute, java.lang.String name, java.lang.String parameter)
double	NominalStatistics.getStatistics(Attribute attribute, java.lang.String name, java.lang.String parameter)
double	MinMaxStatistics.getStatistics(Attribute attribute, java.lang.String name, java.lang.String parameter)
double	ExampleSet.getStatistics(Attribute attribute, java.lang.String statisticsName, java.lang.String statisticsParameter) Returns the desired statistic for the given attribute.
double	Example.getValue(Attribute a) Returns the value of attribute a.
java.lang.String	Example.getValueAsString(Attribute attribute) Returns the value of this attribute as string representation, i.e. the number as string for numerical attributes and the correctly mapped categorical value for nominal values.
java.lang.String	Example.getValueAsString(Attribute attribute, int fractionDigits, boolean quoteNominal) Returns the value of this attribute as string representation, i.e. the number as string for numerical attributes and the correctly mapped categorical value for nominal values.
double	AttributeTransformation.inverseTransform(Attribute attribute, double value)
void	ExampleSet.recalculateAttributeStatistics(Attribute attribute) Recalculate the attribute statistics of the given attribute.
boolean	Attributes.remove(Attribute attribute) Removes the given attribute.
boolean	AbstractAttributes.remove(Attribute attribute)
void	SimpleAttributes.rename(Attribute attribute, java.lang.String newName)
void	DelegateAttributes.rename(Attribute attribute, java.lang.String newName) Deprecated.
void	Attributes.rename(Attribute attribute, java.lang.String newName) Notifies the Attributes that this attribute will rename itself to the given name immediately after this method returns.
Attribute	Attributes.replace(Attribute first, Attribute second) Replaces the first attribute by the second.
Attribute	AbstractAttributes.replace(Attribute first, Attribute second)
static void	Tools.replaceValue(Attribute attribute, java.lang.String oldValue, java.lang.String newValue) Replaces the given real value by the new one.
static void	Tools.replaceValue(ExampleSet exampleSet, Attribute attribute, double oldValue, double newValue) Replaces the given real value by the new one.
static void	Tools.replaceValue(ExampleSet exampleSet, Attribute attribute, java.lang.String oldValue, java.lang.String newValue) Replaces the given value by the new one.
static Attribute	Tools.selectAttribute(Attribute[] attributes, double[] probs, java.util.Random random)
void	AttributeRole.setAttribute(Attribute attribute)
void	Attributes.setCluster(Attribute cluster) Sets the cluster attribute.
void	AbstractAttributes.setCluster(Attribute cluster)
void	Attributes.setCost(Attribute cost) Sets the cost attribute.
void	AbstractAttributes.setCost(Attribute cost)
void	Attributes.setId(Attribute id) Sets the id attribute.
void	AbstractAttributes.setId(Attribute id)
void	Attributes.setLabel(Attribute label) Sets the label attribute.
void	AbstractAttributes.setLabel(Attribute label)
void	Attributes.setOutlier(Attribute outlier) Sets the outlier attribute.
void	AbstractAttributes.setOutlier(Attribute outlier)
void	Attributes.setPredictedLabel(Attribute predictedLabel) Sets the predicted label attribute.
void	AbstractAttributes.setPredictedLabel(Attribute predictedLabel)
void	Attributes.setSpecialAttribute(Attribute attribute, java.lang.String specialName) Sets the special attribute for the given name.
void	AbstractAttributes.setSpecialAttribute(Attribute attribute, java.lang.String specialName)
void	Example.setValue(Attribute a, double value) Sets the value of attribute a.
void	Example.setValue(Attribute a, java.lang.String str) Sets the value of attribute a which must be a nominal attribute.
void	Attributes.setWeight(Attribute weight) Sets the weight attribute.
void	AbstractAttributes.setWeight(Attribute weight)
void	WeightedNumericalStatistics.startCounting(Attribute attribute)
void	UnknownStatistics.startCounting(Attribute attribute)
void	Statistics.startCounting(Attribute attribute)
void	NumericalStatistics.startCounting(Attribute attribute)
void	NominalStatistics.startCounting(Attribute attribute)
void	MinMaxStatistics.startCounting(Attribute attribute)
double	AttributeTransformation.transform(Attribute attribute, double value)

Constructors in com.rapidminer.example with parameters of type Attribute

AttributeDescription(Attribute attribute, java.lang.String name, int valueType, int blockType, double defaultValue, int tableIndex)

AttributeRole(Attribute attribute)

Uses of Attribute in com.rapidminer.example.set

Methods in com.rapidminer.example.set with parameters of type Attribute

void	ReplaceMissingExampleSet.addReplacement(Attribute attribute)
void	AttributeWeightedExampleSet.flipAttributeUsed(Attribute attribute) Flips the selection state of the attribute with the given index.
double	AbstractExampleSet.getStatistics(Attribute attribute, java.lang.String statisticsName) Returns the desired statistic for the given attribute.
double	AbstractExampleSet.getStatistics(Attribute attribute, java.lang.String statisticsName, java.lang.String statisticsParameter) Returns the desired statistic for the given attribute.
double	AttributeWeightedExampleSet.getWeight(Attribute attribute) Returns the weight of the attribute.
double	AttributeTransformationWeighting.inverseTransform(Attribute attribute, double value)
double	AttributeTransformationReplaceMissing.inverseTransform(Attribute attribute, double value)
double	AttributeTransformationRemapping.inverseTransform(Attribute attribute, double value)
boolean	AttributeWeightedExampleSet.isAttributeUsed(Attribute attribute) Returns the selection state of the attribute.
void	AbstractExampleSet.recalculateAttributeStatistics(Attribute attribute) Recalculate the attribute statistics of the given attribute.
void	AttributeWeightedExampleSet.setAttributeUsed(Attribute attribute, boolean selected) Sets the selection state of the attribute.
void	AttributeWeightedExampleSet.setWeight(Attribute attribute, double weightValue) Sets the weight of the attribute.
static SplittedExampleSet	SplittedExampleSet.splitByAttribute(ExampleSet exampleSet, Attribute attribute) Works only for nominal and integer attributes.
static SplittedExampleSet	SplittedExampleSet.splitByAttribute(ExampleSet exampleSet, Attribute attribute, double value) Works only for real-value attributes.
double	AttributeTransformationWeighting.transform(Attribute attribute, double value)
double	AttributeTransformationReplaceMissing.transform(Attribute attribute, double value)
double	AttributeTransformationRemapping.transform(Attribute attribute, double value)

Constructors in com.rapidminer.example.set with parameters of type Attribute

AttributeValueFilter(Attribute attribute, int comparisonType, java.lang.String value)
Creates a new AttributeValueFilter.

AttributeValueFilterSingleCondition(Attribute attribute, int comparisonType, java.lang.String value)
Creates a new AttributeValueFilter.

SortedExampleSet(ExampleSet parent, Attribute sortingAttribute, int sortingDirection)

Constructor parameters in com.rapidminer.example.set with type arguments of type Attribute

SimpleExampleSet(ExampleTable exampleTable, java.util.List<Attribute> regularAttributes)
Constructs a new SimpleExampleSet backed by the given example table.

SimpleExampleSet(ExampleTable exampleTable, java.util.List<Attribute> regularAttributes, java.util.Map<Attribute,java.lang.String> specialAttributes)
Constructs a new SimpleExampleSet backed by the given example table.

SimpleExampleSet(ExampleTable exampleTable, java.util.List<Attribute> regularAttributes, java.util.Map<Attribute,java.lang.String> specialAttributes)
Constructs a new SimpleExampleSet backed by the given example table.

SimpleExampleSet(ExampleTable exampleTable, java.util.Map<Attribute,java.lang.String> specialAttributes)
Constructs a new SimpleExampleSet backed by the given example table.

Uses of Attribute in com.rapidminer.example.table

Classes in com.rapidminer.example.table that implement Attribute

class	AbstractAttribute This is a possible abstract superclass for all attribute implementations.
class	BinominalAttribute This class holds all information on a single binary attribute.
class	DateAttribute This class holds all information on a single date attribute.
class	NominalAttribute This class holds all information on a single nominal attribute.
class	NumericalAttribute This class holds all information on a single numerical attribute.
class	PolynominalAttribute This class holds all information on a single nominal attribute.
class	ViewAttribute A view attribute is based on a ViewModel (Preprocessing Model) and applies the model on the fly.

Methods in com.rapidminer.example.table that return Attribute

static Attribute	AttributeFactory.changeValueType(Attribute attribute, int valueType) Changes the value type of the given attribute and returns a new attribute with the same properties but the new value type.
static Attribute	AttributeFactory.createAttribute(Attribute attribute) Simple clone factory method for attributes.
static Attribute	AttributeFactory.createAttribute(Attribute attribute, java.lang.String functionName) Simple clone factory method for attributes.
static Attribute	AttributeFactory.createAttribute(int valueType) Creates a simple single attribute depending on the given value type.
static Attribute	AttributeFactory.createAttribute(int valueType, int blockType, java.lang.String constructionDescription) Creates a simple attribute depending on the given value type.
static Attribute	AttributeFactory.createAttribute(java.lang.String name, int valueType) Creates a simple single attribute depending on the given value type.
static Attribute	AttributeFactory.createAttribute(java.lang.String name, int valueType, int blockType) Creates a simple attribute depending on the given value type.
Attribute	ExampleTable.findAttribute(java.lang.String name) Returns the attribute with the given name.
Attribute	AbstractExampleTable.findAttribute(java.lang.String name) Returns the attribute with the given name.
Attribute	ExampleTable.getAttribute(int i) Returns the attribute of the column number i.
Attribute	AbstractExampleTable.getAttribute(int i) Returns the attribute of the column number i.
Attribute[]	ExampleTable.getAttributes() Returns a new array containing all Attributes.
Attribute[]	AbstractExampleTable.getAttributes() Returns a new array containing all Attributes.

Methods in com.rapidminer.example.table with parameters of type Attribute

int	MemoryExampleTable.addAttribute(Attribute attribute) Adds a new attribute to this example table by invoking the super method.
int	ExampleTable.addAttribute(Attribute a) Adds the attribute to the list of attributes assigning it a free column index.
int	DatabaseExampleTable.addAttribute(Attribute attribute)
int	AbstractExampleTable.addAttribute(Attribute a) Adds the attribute to the list of attributes assigning it a free column index.
static Attribute	AttributeFactory.changeValueType(Attribute attribute, int valueType) Changes the value type of the given attribute and returns a new attribute with the same properties but the new value type.
DataRow	DataRowFactory.create(java.lang.Double[] data, Attribute[] attributes) Creates a data row from an Object array.
DataRow	DataRowFactory.create(java.lang.Object[] data, Attribute[] attributes) Creates a data row from an Object array.
DataRow	DataRowFactory.create(java.lang.String[] strings, Attribute[] attributes) Creates a data row from an array of Strings.
static Attribute	AttributeFactory.createAttribute(Attribute attribute) Simple clone factory method for attributes.
static Attribute	AttributeFactory.createAttribute(Attribute attribute, java.lang.String functionName) Simple clone factory method for attributes.
ExampleSet	ExampleTable.createExampleSet(Attribute labelAttribute) Returns a new example set with all attributes switched on.
ExampleSet	AbstractExampleTable.createExampleSet(Attribute labelAttribute) Returns a new example set with all attributes switched on.
ExampleSet	ExampleTable.createExampleSet(Attribute labelAttribute, Attribute weightAttribute, Attribute idAttribute) Returns a new example set with all attributes switched on.
ExampleSet	AbstractExampleTable.createExampleSet(Attribute labelAttribute, Attribute weightAttribute, Attribute idAttribute) Returns a new example set with all attributes switched on.
double	DataRow.get(Attribute attribute) Returns the value stored at the given Attribute's index.
double	DatabaseDataRow.get(Attribute attribute) Returns the desired data for the given attribute.
static double	DatabaseDataRow.readColumn(java.sql.ResultSet resultSet, Attribute attribute) Reads the data for the given attribute from the result set.
void	ExampleTable.removeAttribute(Attribute attribute) Equivalent to calling removeAttribute(attribute.getTableIndex()).
void	DatabaseExampleTable.removeAttribute(Attribute attribute)
void	AbstractExampleTable.removeAttribute(Attribute attribute) Equivalent to calling removeAttribute(attribute.getTableIndex()).
void	DataRow.set(Attribute attribute, double value) Sets the value of the Attribute to value.
void	DatabaseDataRow.set(Attribute attribute, double value) Sets the given data for the given attribute.

Method parameters in com.rapidminer.example.table with type arguments of type Attribute

void	MemoryExampleTable.addAttributes(java.util.Collection<Attribute> newAttributes) Adds all Attributes in newAttributes to the end of the list of attributes, creating new data columns if necessary.
void	ExampleTable.addAttributes(java.util.Collection<Attribute> newAttributes) Adds all Attributes in newAttributes to the end of the list of attributes, creating new data columns if necessary.
void	AbstractExampleTable.addAttributes(java.util.Collection<Attribute> newAttributes) Adds all Attributes in newAttributes to the end of the list of attributes, creating new data columns if necessary.
ExampleSet	ExampleTable.createExampleSet(java.util.Map<Attribute,java.lang.String> specialAttributes) Returns a new example set with all attributes switched on.
ExampleSet	AbstractExampleTable.createExampleSet(java.util.Map<Attribute,java.lang.String> specialAttributes) Returns a new example set with all attributes switched on.

Constructors in com.rapidminer.example.table with parameters of type Attribute

RandomDataRowReader(ExampleSet baseExampleSet, Attribute[] attributes, int size)

SimpleArrayDataRowReader(DataRowFactory factory, Attribute[] attributes, java.util.Iterator<SimpleArrayData> simpleData)

ViewAttribute(ViewModel model, Attribute parent, java.lang.String name, int valueType, NominalMapping mapping)

Constructor parameters in com.rapidminer.example.table with type arguments of type Attribute

AbstractExampleTable(java.util.List<Attribute> attributes)
Creates a new ExampleTable.

MemoryExampleTable(java.util.List<Attribute> attributes)
Creates a new instance of MemoryExampleTable.

MemoryExampleTable(java.util.List<Attribute> attributes, DataRowFactory factory, int size)
Creates a new instance of MemoryExampleTable.

MemoryExampleTable(java.util.List<Attribute> attributes, DataRowReader i)
Creates an empty memory example table and fills it with the data rows read from i.

MemoryExampleTable(java.util.List<Attribute> attributes, DataRowReader i, boolean permutate)
Creates an empty memory example table and fills it with the data rows read from i.

RandomExampleTable(ExampleSet baseExampleSet, java.util.List<Attribute> attributes, int size)

ResultSetDataRowReader(DataRowFactory dataRowFactory, java.util.List<Attribute> attributeList, java.sql.ResultSet resultSet)
Constructor.

Uses of Attribute in com.rapidminer.example.test

Methods in com.rapidminer.example.test that return Attribute

static Attribute	ExampleTestTools.attributeDogCatMouse()
static Attribute	ExampleTestTools.attributeInt()
static Attribute	ExampleTestTools.attributeReal()
static Attribute	ExampleTestTools.attributeReal(int index)
static Attribute	ExampleTestTools.attributeYesNo()
static Attribute[]	ExampleTestTools.createFourAttributes() Creates four attributes: "animal" (dog/cat/mouse), "decision" (yes/no), "int", and "real".
static Attribute	ExampleTestTools.createPredictedLabel(ExampleSet exampleSet)

Methods in com.rapidminer.example.test with parameters of type Attribute

static DataRowReader	ExampleTestTools.createDataRowReader(DataRowFactory factory, Attribute[] attributes, java.lang.String[][] values) Returns a DataRowReader returning the given values.
static DataRowReader	ExampleTestTools.createDataRowReader(int size, Attribute[] attributes) Returns a DataRowReader returning random values (generated with fixed random seed).

Uses of Attribute in com.rapidminer.generator

Fields in com.rapidminer.generator declared as Attribute

protected Attribute[]

FeatureGenerator.resultAttributes The attributes of the function(s) calculated by this FeatureGenerator.

Methods in com.rapidminer.generator that return Attribute

Attribute	FeatureGenerator.getArgument(int i) Returns the i-th selected argument (the true index as used in the example set's example table).
Attribute	AttributePeak.getAttribute()
Attribute[]	SingularNumericalGenerator.getInputAttributes()
abstract Attribute[]	FeatureGenerator.getInputAttributes() Returns an array of Attributes where the length is the arity of the generator, [i] is the attribute type of the i-th argument.
Attribute[]	ConstantGenerator.getInputAttributes()
Attribute[]	BinaryNumericalGenerator.getInputAttributes()
Attribute[]	SingularNumericalGenerator.getOutputAttributes(ExampleTable input)
Attribute[]	MinMaxGenerator.getOutputAttributes(ExampleTable input)
abstract Attribute[]	FeatureGenerator.getOutputAttributes(ExampleTable input) Returns the generated attributes types.
Attribute[]	ConstantGenerator.getOutputAttributes(ExampleTable input)
Attribute[]	BinaryNumericalGenerator.getOutputAttributes(ExampleTable input)
Attribute[]	AverageGenerator.getOutputAttributes(ExampleTable input)
Attribute[]	AlgebraicOrGenerator.getOutputAttributes(ExampleTable input)

Methods in com.rapidminer.generator that return types with arguments of type Attribute

static java.util.List<Attribute>

FeatureGenerator.generateAll(ExampleTable exampleTable, java.util.Collection<FeatureGenerator> generatorList) Generates all new attributes and updates the ExampleTable.

Methods in com.rapidminer.generator with parameters of type Attribute

protected boolean	FeatureGenerator.checkCompatibility(Attribute attribute, Attribute compatible, java.lang.String[] functions)
java.util.List<AttributePeak>	SinusFactory.getAttributePeaks(ExampleSet exampleSet, Attribute first, Attribute second) Calculates the fourier transformation from the first attribute on the second and delivers the maxPeaks highest peaks.
void	FeatureGenerator.setArguments(Attribute[] args) Sets the arguments (indices) used in future generate(...)
void	ConstantGenerator.setArguments(Attribute[] args)

Constructors in com.rapidminer.generator with parameters of type Attribute

AttributePeak(Attribute attribute, double frequency, double evidence)

Uses of Attribute in com.rapidminer.operator

Methods in com.rapidminer.operator with parameters of type Attribute

double

ViewModel.getValue(Attribute targetAttribute, double value) This method has to provide the attribute value mapping for the view.

Uses of Attribute in com.rapidminer.operator.clustering

Methods in com.rapidminer.operator.clustering with parameters of type Attribute

void	WekaClusterModel.applyModelForInstance(weka.core.Instance instance, Example e, Attribute clusterAtt) Clusters ervery weka instance and sets the result as cluster index of the current example.

Uses of Attribute in com.rapidminer.operator.features.aggregation

Methods in com.rapidminer.operator.features.aggregation with parameters of type Attribute

ExampleSet

AggregationIndividual.createExampleSet(ExampleSet originalExampleSet, Attribute[] allAttributes, FeatureGenerator generator)

Constructors in com.rapidminer.operator.features.aggregation with parameters of type Attribute

AggregationPopulationPlotter(ExampleSet originalExampleSet, Attribute[] allAttributes, FeatureGenerator generator)
Creates plotter panel which is repainted every generation.

Uses of Attribute in com.rapidminer.operator.features.construction

Constructors in com.rapidminer.operator.features.construction with parameters of type Attribute

DirectedGeneratingMutation(Attribute[] originalAttributes, double p, java.util.List generators, int maxGeneratedAttributes, int maxAddedOriginalAttributes, java.lang.String[] unusableFunctions, RandomGenerator random)

Constructor parameters in com.rapidminer.operator.features.construction with type arguments of type Attribute

FourierGeneratingMutation(java.util.List<Attribute> originalAttributes, double p, java.util.List<FeatureGenerator> generators, int numberOfConstructed, int numberOfOriginal, int maxPeaks, int adaptionType, int attributesPerPeak, double epsilon, java.lang.String[] unusableFunctions, RandomGenerator random)

GeneratingMutation(java.util.List<Attribute> originalAttributes, double prob, int maxNumberOfAttributes, java.util.List<FeatureGenerator> generators, RandomGenerator random)

Uses of Attribute in com.rapidminer.operator.generator

Methods in com.rapidminer.operator.generator that return Attribute

Attribute	TwoGaussiansClassificationFunction.getLabel()
Attribute	TransactionDatasetFunction.getLabel()
Attribute	TargetFunction.getLabel() Returns the label attribute.
Attribute	SpiralClusteringFunction.getLabel()
Attribute	RingClusteringFunction.getLabel()
Attribute	RegressionFunction.getLabel()
Attribute	MultiClassificationFunction.getLabel()
Attribute	GridFunction.getLabel()
Attribute	GaussianMixtureFunction.getLabel()
Attribute	GaussianFunction.getLabel()
Attribute	DrillerOscillationFunction.getLabel()
Attribute	ClassificationFunction.getLabel()

Uses of Attribute in com.rapidminer.operator.io

Methods in com.rapidminer.operator.io with parameters of type Attribute

abstract void	ResultSetExampleSource.setNominalValues(java.util.List<Attribute> attributeList, java.sql.ResultSet resultSet, Attribute label) Since the ResultSet does not provide information about possible values of nominal attributes, subclasses must set these by implementing this method.
void	KDBExampleSource.setNominalValues(java.util.List attributeList, java.sql.ResultSet resultSet, Attribute label)
void	DatabaseExampleSource.setNominalValues(java.util.List attributeList, java.sql.ResultSet resultSet, Attribute label)

Method parameters in com.rapidminer.operator.io with type arguments of type Attribute

abstract void

ResultSetExampleSource.setNominalValues(java.util.List<Attribute> attributeList, java.sql.ResultSet resultSet, Attribute label) Since the ResultSet does not provide information about possible values of nominal attributes, subclasses must set these by implementing this method.

Uses of Attribute in com.rapidminer.operator.learner

Methods in com.rapidminer.operator.learner that return Attribute

static Attribute	PredictionModel.createPredictedLabel(ExampleSet exampleSet, Attribute label) Creates a predicted label for the given example set based on the label attribute defined for this prediction model.
Attribute	PredictionModel.getLabel() Returns the label attribute.

Methods in com.rapidminer.operator.learner with parameters of type Attribute

static Attribute	PredictionModel.createPredictedLabel(ExampleSet exampleSet, Attribute label) Creates a predicted label for the given example set based on the label attribute defined for this prediction model.
ExampleSet	SimplePredictionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Iterates over all examples and applies the model to them.
ExampleSet	SimpleBinaryPredictionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Iterates over all examples and applies the model to them.
abstract ExampleSet	PredictionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Subclasses should iterate through the given example set and set the prediction for each example.

Uses of Attribute in com.rapidminer.operator.learner.associations

Constructors in com.rapidminer.operator.learner.associations with parameters of type Attribute

BooleanAttributeItem(Attribute item)

Uses of Attribute in com.rapidminer.operator.learner.bayes

Methods in com.rapidminer.operator.learner.bayes with parameters of type Attribute

ExampleSet	SimpleDistributionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	KernelDistributionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Perform predictions based on the distribution properties.
abstract ExampleSet	DistributionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	SimpleDistributionModel.performPredictionOld(ExampleSet exampleSet, Attribute predictedLabel) Perform predictions based on the distribution properties.

Uses of Attribute in com.rapidminer.operator.learner.functions

Methods in com.rapidminer.operator.learner.functions with parameters of type Attribute

ExampleSet	LinearRegressionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	FastMarginModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)

Uses of Attribute in com.rapidminer.operator.learner.functions.kernel

Methods in com.rapidminer.operator.learner.functions.kernel with parameters of type Attribute

SVMInterface	MyKLRLearner.createSVM(Attribute label, Kernel kernel, SVMExamples sVMExamples, ExampleSet rapidMinerExamples)
SVMInterface	JMySVMLearner.createSVM(Attribute label, Kernel kernel, SVMExamples sVMExamples, ExampleSet rapidMinerExamples)
abstract SVMInterface	AbstractMySVMLearner.createSVM(Attribute label, Kernel kernel, SVMExamples svmExamples, ExampleSet rapidMinerExamples) Creates a new SVM according to the given label.
ExampleSet	RVMModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	LibSVMModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	KernelLogisticRegressionModel.performPrediction(ExampleSet exampleSet, Attribute predLabel) Applies the model to each example of the example set.
ExampleSet	GPModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	AbstractMySVMModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute)

Uses of Attribute in com.rapidminer.operator.learner.functions.kernel.evosvm

Methods in com.rapidminer.operator.learner.functions.kernel.evosvm with parameters of type Attribute

ExampleSet

EvoSVMModel.performPrediction(ExampleSet exampleSet, Attribute predLabel) Applies the model to each example of the example set.

Uses of Attribute in com.rapidminer.operator.learner.functions.kernel.hyperhyper

Methods in com.rapidminer.operator.learner.functions.kernel.hyperhyper with parameters of type Attribute

ExampleSet

HyperModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)

Uses of Attribute in com.rapidminer.operator.learner.functions.kernel.jmysvm.examples

Constructors in com.rapidminer.operator.learner.functions.kernel.jmysvm.examples with parameters of type Attribute

SVMExamples(ExampleSet exampleSet, Attribute labelAttribute, boolean scale)

SVMExamples(ExampleSet exampleSet, Attribute labelAttribute, java.util.Map<java.lang.Integer,SVMExamples.MeanVariance> meanVariances)
Creates a fresh example set of the given size from the RapidMiner example reader.

Uses of Attribute in com.rapidminer.operator.learner.functions.neuralnet

Methods in com.rapidminer.operator.learner.functions.neuralnet with parameters of type Attribute

ExampleSet	SimpleNeuralNetModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	NeuralNetModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	ImprovedNeuralNetModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
void	InputNode.setAttribute(Attribute attribute, double attributeRange, double attributeBase, boolean normalize)

Constructors in com.rapidminer.operator.learner.functions.neuralnet with parameters of type Attribute

OutputNode(java.lang.String nodeName, Attribute label, double labelRange, double labelBase)

Uses of Attribute in com.rapidminer.operator.learner.igss.hypothesis

Fields in com.rapidminer.operator.learner.igss.hypothesis declared as Attribute

protected static Attribute[]

GSSModel.regularAttributes The regular attributes used by all rules.

Methods in com.rapidminer.operator.learner.igss.hypothesis that return Attribute

Attribute	Literal.getAttribute() Returns the attribute of this literals.
Attribute	Hypothesis.getLabel() Returns the label.

Methods in com.rapidminer.operator.learner.igss.hypothesis with parameters of type Attribute

ExampleSet

GSSModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Iterates over all examples and applies the model to them.

Constructors in com.rapidminer.operator.learner.igss.hypothesis with parameters of type Attribute

Hypothesis(Attribute[] regulars, Attribute l, boolean rs, boolean createAll)
Create a new dummy hypothesis to allow calling the 'init' method, initialize the regularAttributes, label and p0 fields.

Hypothesis(Attribute[] regulars, Attribute l, boolean rs, boolean createAll)
Create a new dummy hypothesis to allow calling the 'init' method, initialize the regularAttributes, label and p0 fields.

Literal(Attribute a, int v)
Constructs a new Literal.

Literal(Attribute a, int v, int i)
Constructs a new Literal.

Rule(Attribute[] regularAttributes, Attribute label, boolean rejectionSampling, boolean createAll)
Creates a new rule,initializes the regularAttributes and the literals attribute.

Rule(Attribute[] regularAttributes, Attribute label, boolean rejectionSampling, boolean createAll)
Creates a new rule,initializes the regularAttributes and the literals attribute.

Uses of Attribute in com.rapidminer.operator.learner.lazy

Methods in com.rapidminer.operator.learner.lazy with parameters of type Attribute

ExampleSet	KNNRegressionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	KNNClassificationModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	DefaultModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute) Iterates over all examples and applies the model to them.
ExampleSet	AttributeBasedVotingModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute)

Uses of Attribute in com.rapidminer.operator.learner.meta

Methods in com.rapidminer.operator.learner.meta that return Attribute

protected Attribute

SDEnsemble.createPredictedLabel(ExampleSet exampleSet) Creates a predicted label with the given name.

Methods in com.rapidminer.operator.learner.meta with parameters of type Attribute

static int	SDRulesetInduction.getPosIndex(Attribute label)
ExampleSet	TransformedRegressionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute) Iterates over all examples and applies this model.
ExampleSet	ThresholdModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	StackingModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	SDEnsemble.performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute) Iterates over all models and returns the class with maximum likelihood.
ExampleSet	RelativeRegressionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	MultiModelByRegression.performPrediction(ExampleSet exampleSet, Attribute predictedLabelAttribute) Iterates over all classes of the label and applies one model for each class.
ExampleSet	MultiModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Iterates over all classes of the label and applies one model for each class.
ExampleSet	MetaCostModel.performPrediction(ExampleSet originalExampleSet, Attribute predictedLabel)
ExampleSet	Binary2MultiClassModel.performPrediction(ExampleSet originalExampleSet, Attribute predictedLabel) Chooses the right evaluation procedure depending on classificationType.
ExampleSet	BayBoostModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel) Iterates over all models and returns the class with maximum likelihood.
ExampleSet	BaggingModel.performPrediction(ExampleSet origExampleSet, Attribute predictedLabel) Iterates over all models and averages confidences.
ExampleSet	AdditiveRegressionModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)
ExampleSet	AdaBoostModel.performPrediction(ExampleSet origExampleSet, Attribute predictedLabel) Iterates over all models and returns the class with maximum likelihood.

Constructors in com.rapidminer.operator.learner.meta with parameters of type Attribute

BayBoostStream.BatchFilterCondition(Attribute attribute, int batchNumber)

Uses of Attribute in com.rapidminer.operator.learner.rules

Fields in com.rapidminer.operator.learner.rules declared as Attribute

protected Attribute	AbstractCriterion.labelAttribute
protected Attribute	AbstractCriterion.weightAttribute

Methods in com.rapidminer.operator.learner.rules that return Attribute

Attribute

ConjunctiveRuleModel.getAttributeOfLiteral(int literalNumber)

Methods in com.rapidminer.operator.learner.rules with parameters of type Attribute

Split	NumericalSplitter.getBestSplit(ExampleSet inputSet, Attribute attribute, java.lang.String labelName)
protected int	ConjunctiveRuleModel.getFirstUnusedAttribute(ExampleSet exampleSet, Attribute[] allAttributes) Helper method of getAllRefinedRules.
int	ConjunctiveRuleModel.getPositionOfAttributeInRule(Attribute attribute)

Constructors in com.rapidminer.operator.learner.rules with parameters of type Attribute

ConjunctiveRuleModel(ConjunctiveRuleModel ruleToExtend, Attribute attribute, double testValue)
Constructor to create an empty rule that makes a default prediction

Uses of Attribute in com.rapidminer.operator.learner.subgroups.hypothesis

Methods in com.rapidminer.operator.learner.subgroups.hypothesis that return Attribute

Attribute

Literal.getAttribute()

Methods in com.rapidminer.operator.learner.subgroups.hypothesis with parameters of type Attribute

java.util.LinkedList<Rule>

Hypothesis.generateRules(int ruleGenerationMode, Attribute label)

Method parameters in com.rapidminer.operator.learner.subgroups.hypothesis with type arguments of type Attribute

java.util.LinkedList<Hypothesis>	Hypothesis.refine(java.lang.Iterable<Attribute> attributes)
java.util.LinkedList<Hypothesis>	Hypothesis.restrictedRefine(java.lang.Iterable<Attribute> attributes)

Constructors in com.rapidminer.operator.learner.subgroups.hypothesis with parameters of type Attribute

Literal(Attribute attribute, double value)

Uses of Attribute in com.rapidminer.operator.learner.tree

Fields in com.rapidminer.operator.learner.tree declared as Attribute

protected Attribute	AbstractCriterion.labelAttribute
protected Attribute	AbstractCriterion.weightAttribute

Methods in com.rapidminer.operator.learner.tree that return Attribute

Attribute

Benefit.getAttribute()

Methods in com.rapidminer.operator.learner.tree with parameters of type Attribute

Benefit	TreeBuilder.calculateBenefit(ExampleSet trainingSet, Attribute attribute) This method calculates the benefit of the given attribute.
protected Benefit	CHAIDLearner.calculateBenefit(ExampleSet trainingSet, Attribute attribute) This method calculates the benefit of the given attribute.
double	NumericalSplitter.getBestSplit(ExampleSet inputSet, Attribute attribute)
double	InfoGainCriterion.getNominalBenefit(ExampleSet exampleSet, Attribute attribute)
double	GiniIndexCriterion.getNominalBenefit(ExampleSet exampleSet, Attribute attribute)
double	GainRatioCriterion.getNominalBenefit(ExampleSet exampleSet, Attribute attribute)
double	Criterion.getNominalBenefit(ExampleSet exampleSet, Attribute attribute)
double	AccuracyCriterion.getNominalBenefit(ExampleSet exampleSet, Attribute attribute)
double[][]	FrequencyCalculator.getNominalWeightCounts(ExampleSet exampleSet, Attribute attribute)
double	InfoGainCriterion.getNumericalBenefit(ExampleSet exampleSet, Attribute attribute, double splitValue)
double	GiniIndexCriterion.getNumericalBenefit(ExampleSet exampleSet, Attribute attribute, double splitValue)
double	GainRatioCriterion.getNumericalBenefit(ExampleSet exampleSet, Attribute attribute, double splitValue)
double	Criterion.getNumericalBenefit(ExampleSet exampleSet, Attribute attribute, double splitValue)
double	AccuracyCriterion.getNumericalBenefit(ExampleSet exampleSet, Attribute attribute, double splitValue)
double[][]	FrequencyCalculator.getNumericalWeightCounts(ExampleSet exampleSet, Attribute attribute, double splitValue)

Constructors in com.rapidminer.operator.learner.tree with parameters of type Attribute

Benefit(double benefit, Attribute attribute)

Benefit(double benefit, Attribute attribute, double splitValue)

GreaterSplitCondition(Attribute attribute, double value)

LessEqualsSplitCondition(Attribute attribute, double value)

MultiCriterionDecisionStumps.DecisionStumpModel(Attribute attribute, double testValue, ExampleSet exampleSet, boolean prediction, boolean includeNaNs)

NominalSplitCondition(Attribute attribute, java.lang.String valueString)

Uses of Attribute in com.rapidminer.operator.learner.weka

Methods in com.rapidminer.operator.learner.weka with parameters of type Attribute

void	WekaClassifier.applyModelForInstance(weka.core.Instance instance, Example e, Attribute predictedLabelAttribute) Classifies ervery weka instance and sets the result as predicted label of the current example.
ExampleSet	WekaClassifier.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)

Uses of Attribute in com.rapidminer.operator.performance

Methods in com.rapidminer.operator.performance with parameters of type Attribute

protected double[]	UserBasedPerformanceEvaluator.getClassWeights(Attribute label) Returns null.
protected double[]	SimplePerformanceEvaluator.getClassWeights(Attribute label) Returns null.
protected double[]	RegressionPerformanceEvaluator.getClassWeights(Attribute label)
protected double[]	PolynominalClassificationPerformanceEvaluator.getClassWeights(Attribute label)
protected double[]	PerformanceEvaluator.getClassWeights(Attribute label)
protected double[]	ForecastingPerformanceEvaluator.getClassWeights(Attribute label)
protected double[]	BinominalClassificationPerformanceEvaluator.getClassWeights(Attribute label) Returns null.
protected abstract double[]	AbstractPerformanceEvaluator.getClassWeights(Attribute label) Delivers class weights for performance criteria which implement the ClassWeightedPerformance interface.
static double[]	RankStatistics.rank(ExampleSet eSet, Attribute att, Attribute mappingAtt) Calculates ranks for an attribute.
static double[]	RankStatistics.rank(ExampleSet eSet, Attribute att, Attribute mappingAtt, double fuzz) Calculates ranks for an attribute.
static double	RankStatistics.rho(ExampleSet eSet, Attribute a, Attribute b) Calculates the Spearman rank correlation between two attributes.
static double	RankStatistics.rho(ExampleSet eSet, Attribute a, Attribute b, double f) Calculates the Spearman rank correlation between two attributes.
static double	RankStatistics.tau_b(ExampleSet eSet, Attribute a, Attribute b) Computes Kendall's tau-b rank correlation statistic, ignoring examples containing missing values.
static double	RankStatistics.tau_b(ExampleSet eSet, Attribute a, Attribute b, double fuzz) Computes Kendall's tau-b rank correlation statistic, ignoring examples containing missing values, with approximate comparisons.

Uses of Attribute in com.rapidminer.operator.performance.cost

Constructors in com.rapidminer.operator.performance.cost with parameters of type Attribute

ClassificationCostCriterion(double[][] costMatrix, Attribute label, Attribute predictedLabel)

Uses of Attribute in com.rapidminer.operator.postprocessing

Methods in com.rapidminer.operator.postprocessing with parameters of type Attribute

static PlattParameters	PlattScaling.computeParameters(ExampleSet exampleSet, Attribute label) Implementation of Platt' scaling algorithm as found in [Platt, 1999].
ExampleSet	PlattScalingModel.performPrediction(ExampleSet exampleSet, Attribute predictedLabel)

Uses of Attribute in com.rapidminer.operator.preprocessing.discretization

Methods in com.rapidminer.operator.preprocessing.discretization with parameters of type Attribute

double

DiscretizationModel.getValue(Attribute targetAttribute, double value)

Method parameters in com.rapidminer.operator.preprocessing.discretization with type arguments of type Attribute

void	DiscretizationModel.setRanges(java.util.Map<Attribute,double[]> rangesMap, java.lang.String rangeName, int rangeNameType, int numberOfDigits) Creates the ranges.

Uses of Attribute in com.rapidminer.operator.preprocessing.filter

Methods in com.rapidminer.operator.preprocessing.filter that return Attribute

Attribute[]	MissingValueImputation.getOrderedAttributes(ExampleSet exampleSet, int order, boolean ascending)
protected Attribute	NumericToNominal.makeAttribute()
protected Attribute	NumericToBinominal.makeAttribute()

Methods in com.rapidminer.operator.preprocessing.filter with parameters of type Attribute

abstract double	ValueReplenishment.getReplenishmentValue(int functionIndex, ExampleSet baseExampleSet, Attribute attribute, double currentValue, java.lang.String valueString) Returns the value of the replenishment function with the given index.
double	MissingValueReplenishment.getReplenishmentValue(int functionIndex, ExampleSet exampleSet, Attribute attribute, double currentValue, java.lang.String valueString)
double	InfiniteValueReplenishment.getReplenishmentValue(int functionIndex, ExampleSet exampleSet, Attribute attribute, double currentValue, java.lang.String valueString) Replaces the values
double	NominalToBinominalModel.getValue(Attribute targetAttribute, double value)
double	Dictionary.getValue(Attribute targetAttribute, double value)
protected void	NumericToPolynominal.setValue(Example example, Attribute newAttribute, double value)
protected abstract void	NumericToNominal.setValue(Example example, Attribute newAttribute, double value)
protected void	NumericToFormattedNominal.setValue(Example example, Attribute newAttribute, double value)
protected void	NumericToBinominal.setValue(Example example, Attribute newAttribute, double value)

Uses of Attribute in com.rapidminer.operator.preprocessing.filter.attributes

Methods in com.rapidminer.operator.preprocessing.filter.attributes with parameters of type Attribute

AttributeFilterCondition.ScanResult	NumericValueAttributeFilter.beforeScanCheck(Attribute attribute) Don't remove any attribute without checking values
AttributeFilterCondition.ScanResult	NumericalAttributeFilter.beforeScanCheck(Attribute attribute)
AttributeFilterCondition.ScanResult	NoMissingValuesAttributeFilter.beforeScanCheck(Attribute attribute)
AttributeFilterCondition.ScanResult	NominalAttributeFilter.beforeScanCheck(Attribute attribute)
AttributeFilterCondition.ScanResult	NameAttributeFilter.beforeScanCheck(Attribute attribute)
AttributeFilterCondition.ScanResult	MissingValuesAttributeFilter.beforeScanCheck(Attribute attribute)
AttributeFilterCondition.ScanResult	DateAttributeFilter.beforeScanCheck(Attribute attribute)
AttributeFilterCondition.ScanResult	AttributeFilterCondition.beforeScanCheck(Attribute attribute) This method initializes this condition and resets all counters.
AttributeFilterCondition.ScanResult	NumericValueAttributeFilter.check(Attribute attribute, Example example)
AttributeFilterCondition.ScanResult	NoMissingValuesAttributeFilter.check(Attribute attribute, Example example)
AttributeFilterCondition.ScanResult	MissingValuesAttributeFilter.check(Attribute attribute, Example example)
AttributeFilterCondition.ScanResult	AttributeFilterCondition.check(Attribute attribute, Example example) This method checks the given example.
AttributeFilterCondition.ScanResult	AbstractAttributeFilterCondition.check(Attribute attribute, Example example)

Uses of Attribute in com.rapidminer.operator.preprocessing.join

Fields in com.rapidminer.operator.preprocessing.join declared as Attribute

protected Attribute

AbstractExampleSetJoin.AttributeSource.attribute

Methods in com.rapidminer.operator.preprocessing.join that return Attribute

protected Attribute

AbstractExampleSetJoin.AttributeSource.getAttribute()

Methods in com.rapidminer.operator.preprocessing.join with parameters of type Attribute

boolean

AbstractExampleSetJoin.containsAttribute(java.util.List<Attribute> attributeList, Attribute attribute) Returns true if the list already contains an attribute with the given name.

Method parameters in com.rapidminer.operator.preprocessing.join with type arguments of type Attribute

boolean	AbstractExampleSetJoin.containsAttribute(java.util.List<Attribute> attributeList, Attribute attribute) Returns true if the list already contains an attribute with the given name.
protected MemoryExampleTable	ExampleSetJoin.joinData(ExampleSet leftExampleSet, ExampleSet rightExampleSet, java.util.List<AbstractExampleSetJoin.AttributeSource> originalAttributeSources, java.util.List<Attribute> unionAttributeList)
protected MemoryExampleTable	ExampleSetCartesian.joinData(ExampleSet es1, ExampleSet es2, java.util.List<AbstractExampleSetJoin.AttributeSource> originalAttributeSources, java.util.List<Attribute> unionAttributeList) Joins the data WITHOUT a WHERE criteria.
protected abstract MemoryExampleTable	AbstractExampleSetJoin.joinData(ExampleSet es1, ExampleSet es2, java.util.List<AbstractExampleSetJoin.AttributeSource> originalAttributeSources, java.util.List<Attribute> unionAttributeList)

Constructors in com.rapidminer.operator.preprocessing.join with parameters of type Attribute

AbstractExampleSetJoin.AttributeSource(int source, Attribute attribute)

Uses of Attribute in com.rapidminer.operator.preprocessing.normalization

Methods in com.rapidminer.operator.preprocessing.normalization with parameters of type Attribute

double	ZTransformationModel.getValue(Attribute targetAttribute, double value)
double	ProportionNormalizationModel.getValue(Attribute targetAttribute, double value)
double	MinMaxNormalizationModel.getValue(Attribute targetAttribute, double value)

Uses of Attribute in com.rapidminer.operator.preprocessing.series

Methods in com.rapidminer.operator.preprocessing.series that return Attribute

Attribute	UnivariateSeries2WindowExamples.createLabel(ExampleSet exampleSet, int representation)
abstract Attribute	Series2WindowExamples.createLabel(ExampleSet exampleSet, int representation) Subclasses have to override this method.
Attribute	MultivariateSeries2WindowExamples.createLabel(ExampleSet exampleSet, int representation)

Methods in com.rapidminer.operator.preprocessing.series with parameters of type Attribute

void	UnivariateSeries2WindowExamples.fillSeriesExampleTable(MemoryExampleTable table, ExampleSet exampleSet, Attribute idAttribute, int representation, int windowWidth, int stepSize, int horizon)
abstract void	Series2WindowExamples.fillSeriesExampleTable(MemoryExampleTable table, ExampleSet exampleSet, Attribute idAttribute, int representation, int width, int stepSize, int horizon) The given label attribute might be null.
void	MultivariateSeries2WindowExamples.fillSeriesExampleTable(MemoryExampleTable table, ExampleSet exampleSet, Attribute idAttribute, int representation, int windowWidth, int stepSize, int horizon)
java.lang.String	UnivariateSeries2WindowExamples.getNameForAttribute(Attribute[] originalAttributeArray, int representation, int windowWidth, int horizon, int totalCounter)
abstract java.lang.String	Series2WindowExamples.getNameForAttribute(Attribute[] originalAttributeArray, int representation, int windowWidth, int horizon, int totalCounter)
java.lang.String	MultivariateSeries2WindowExamples.getNameForAttribute(Attribute[] originalAttributeArray, int representation, int windowWidth, int horizon, int totalCounter)

Uses of Attribute in com.rapidminer.operator.visualization

Methods in com.rapidminer.operator.visualization with parameters of type Attribute

void	DataStatistics.addInfo(ExampleSet exampleSet, Attribute attribute)

Uses of Attribute in com.rapidminer.operator.visualization.dependencies

Methods in com.rapidminer.operator.visualization.dependencies with parameters of type Attribute

double	MutualInformationMatrixOperator.getMatrixValue(ExampleSet exampleSet, Attribute firstAttribute, Attribute secondAttribute) Calculates the mutual information for both attributes.
abstract double	AbstractPairwiseMatrixOperator.getMatrixValue(ExampleSet exampleSet, Attribute firstAttribute, Attribute secondAttribute)

Uses of Attribute in com.rapidminer.tools.att

Methods in com.rapidminer.tools.att that return Attribute

Attribute	AttributeDataSource.getAttribute()
Attribute	AttributeSet.getAttribute(int index) Returns an attribute by index.
Attribute	AttributeSet.getSpecialAttribute(java.lang.String name) Returns a special attribute by name.

Methods in com.rapidminer.tools.att that return types with arguments of type Attribute

java.util.List<Attribute>	AttributeSet.getAllAttributes() Returns a list of all, i.e. regular and special attributes.
java.util.List<Attribute>	AttributeSet.getRegularAttributes() Returns a list of all regular attributes.
java.util.Map<java.lang.String,Attribute>	AttributeSet.getSpecialAttributes() Returns a Map mapping names to special attributes.

Methods in com.rapidminer.tools.att with parameters of type Attribute

void	AttributeSet.addAttribute(Attribute attribute) Adds an attribute at the end of the list.
void	AttributeDataSource.setAttribute(Attribute attribute)
void	AttributeSet.setSpecialAttribute(java.lang.String name, Attribute attribute) Adds a named special attribute.

Constructors in com.rapidminer.tools.att with parameters of type Attribute

AttributeDataSource(Attribute attribute, java.io.File file, int column, java.lang.String attributeType)

Constructor parameters in com.rapidminer.tools.att with type arguments of type Attribute

AttributeSet(java.util.List<Attribute> regularAttributes, java.util.Map<java.lang.String,Attribute> specialAttributes)

AttributeSet(java.util.List<Attribute> regularAttributes, java.util.Map<java.lang.String,Attribute> specialAttributes)

Uses of Attribute in com.rapidminer.tools.jdbc

Methods in com.rapidminer.tools.jdbc that return types with arguments of type Attribute

static java.util.List<Attribute>

DatabaseHandler.createAttributes(java.sql.ResultSet rs) Creates a list of attributes reflecting the result set's column meta data.

Methods in com.rapidminer.tools.jdbc with parameters of type Attribute

void	DatabaseHandler.addColumn(Attribute attribute, java.lang.String tableName) Adds a column for the given attribute to the table with name tableName.
static java.lang.String	DatabaseHandler.getDatabaseName(Attribute attribute) Deprecated. Use the open and close quotes for identifiers from the properties instead
void	DatabaseHandler.removeColumn(Attribute attribute, java.lang.String tableName) Removes the column of the given attribute from the table with name tableName.

Uses of Attribute in com.rapidminer.tools.math

Methods in com.rapidminer.tools.math with parameters of type Attribute

static double	MathFunctions.correlation(ExampleSet exampleSet, Attribute firstAttribute, Attribute secondAttribute, boolean squared) This method calculates the correlation between two (numerical) attributes of an example set.
Complex[]	FastFourierTransform.getFourierTransform(ExampleSet exampleSet, Attribute source, Attribute target) Builds the fourier transform from the values of the first attribute onto the second.

Uses of Attribute in com.rapidminer.tools.math.function.aggregation

Methods in com.rapidminer.tools.math.function.aggregation with parameters of type Attribute

boolean	VarianceFunction.supportsAttribute(Attribute attribute)
boolean	SumFunction.supportsAttribute(Attribute attribute)
boolean	ModeFunction.supportsAttribute(Attribute attribute)
boolean	MinFunction.supportsAttribute(Attribute attribute)
boolean	MedianFunction.supportsAttribute(Attribute attribute)
boolean	MaxFunction.supportsAttribute(Attribute attribute)
boolean	CountFunction.supportsAttribute(Attribute attribute)
boolean	AverageFunction.supportsAttribute(Attribute attribute)
boolean	AggregationFunction.supportsAttribute(Attribute attribute) Returns whether this function supports the given attribute.