Uses of Interface
com.rapidminer.operator.IOObject

Packages that use IOObject

com.rapidminer	The main packages of RapidMiner.
com.rapidminer.example	The data core classes of RapidMiner.
com.rapidminer.example.set	The available views (example sets) on the example tables.
com.rapidminer.gui.renderer	This package consists the base classes for the renderers / visualization components of RapidMiner components and results.
com.rapidminer.operator	Provides operators for machine learning and data pre-processing.
com.rapidminer.operator.clustering	The base classes for clustering.
com.rapidminer.operator.clustering.clusterer	The operators for clustering.
com.rapidminer.operator.features	Provides feature handling operators.
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.features.selection	Provides operators for automatic feature selection.
com.rapidminer.operator.features.transformation	Provides operators for feature space transformations like PCA or ICA.
com.rapidminer.operator.features.weighting	Operators to weight features or determine feature relevance.
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.associations.fpgrowth	This package contains classes and operators for association rule mining and frequent item set mining based on FPGrowth.
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.neuralnet	This package contains a neural net learner based on Joone.
com.rapidminer.operator.learner.igss	Provides classes for learning operator Iterating Generic Sequential Sampling.
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	Provides the major classes of a subgroup 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.meta	Provides operators for experiment iteration, meta operators, and optimization.
com.rapidminer.operator.meta.branch	Provides operators for conditioned branching.
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	Operators for preprocessing purposes.
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.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.sampling	Preprocessing operators used for sampling.
com.rapidminer.operator.preprocessing.series.filter	Containing preprocessing operators for (time) series filtering.
com.rapidminer.operator.preprocessing.transformation	This package contains some simple operators for basic transformations like grouping, aggregation and pivotization.
com.rapidminer.operator.similarity	Basic framework for similarities.
com.rapidminer.operator.text	This package contains operators and objects to work on texts.
com.rapidminer.operator.validation	Operators for estimation of the performance which can be achieved by learning schemes (and other predictive operators).
com.rapidminer.operator.validation.clustering	Evaluation methods for clustering.
com.rapidminer.operator.validation.clustering.exampledistribution	Evaluation methods for clustering based on the distribution of examples.
com.rapidminer.operator.validation.significance	Statistical significance like ANOVA or t-tests.
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.test	Provides test classes.
com.rapidminer.tools	Provides tools for RapidMiner like parsers for the input files.
com.rapidminer.tools.math	Several tool classes for mathematical operations.

Uses of IOObject in com.rapidminer

Methods in com.rapidminer that return IOObject

IOObject

Process.retrieve(java.lang.String name, boolean remove) Retrieves the stored object.

Methods in com.rapidminer with parameters of type IOObject

void	Process.store(java.lang.String name, IOObject object) Returns the macro handler.

Uses of IOObject in com.rapidminer.example

Subinterfaces of IOObject in com.rapidminer.example

interface

ExampleSet Interface definition for all example sets.

Classes in com.rapidminer.example that implement IOObject

class	AttributeWeight Helper class containing the name of an attribute and the corresponding weight.
class	AttributeWeights AttributeWeights holds the information about the weights of attributes of an example set.

Uses of IOObject in com.rapidminer.example.set

Classes in com.rapidminer.example.set that implement IOObject

class	AbstractExampleSet Implements wrapper methods of abstract example set.
class	AttributeSelectionExampleSet An implementation of ExampleSet that is only a fixed view on a selection of attributes of the parent example set.
class	AttributeWeightedExampleSet An implementation of ExampleSet that allows the weighting of the attributes.
class	ConditionedExampleSet Hides Examples that do not fulfill a given Condition.
class	HeaderExampleSet This example set is a clone of the attributes without reference to any data.
class	MappedExampleSet This example set uses a mapping of indices to access the examples provided by the parent example set.
class	ModelViewExampleSet This is a generic example set (view on the view stack of the data) which can be used to apply any preprocessing model and create a view from it.
class	NonSpecialAttributesExampleSet This example set treats all special attributes as regular attributes.
class	RemappedExampleSet This example set uses the mapping given by another example set and "remaps" on the fly the nominal values according to the given set.
class	ReplaceMissingExampleSet An implementation of ExampleSet that allows the replacement of missing values on the fly.
class	SimilarityExampleSet This similarity based example set is used for the operator ExampleSet2SimilarityExampleSet.
class	SimpleExampleSet A simple implementation of ExampleSet containing a list of attributes and a special attribute map.
class	SingleExampleExampleSet This view can be used to wrap a single example.
class	SortedExampleSet This example set uses a mapping of indices to access the examples provided by the parent example set.
class	SplittedExampleSet An example set that can be split into subsets by using a Partition.

Methods in com.rapidminer.example.set that return IOObject

IOObject

AbstractExampleSet.copy()

Uses of IOObject in com.rapidminer.gui.renderer

Methods in com.rapidminer.gui.renderer that return types with arguments of type IOObject

static java.lang.Class<IOObject>

RendererService.getSuperType(java.lang.String name)

Uses of IOObject in com.rapidminer.operator

Subinterfaces of IOObject in com.rapidminer.operator

interface	Model Model is the interface for all objects which change a data set.
interface	ResultObject This interface extends IOObject and is hence an object which can be handled by operators.
interface	ViewModel The view model is typically used for preprocessing models.

Classes in com.rapidminer.operator that implement IOObject

class	AbstractIOObject This is an abstract superclass for all IOObject.
class	AbstractModel Abstract model is the superclass for all objects which change a data set.
class	GroupedModel This model is a container for all models which should be applied in a sequence.
class	ResultObjectAdapter An adapter class for the interface ResultObject.
class	SimpleResultObject A SimpleResulObject is only a helper class for very simple results with only a name and descriptive text.

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

<T extends IOObject> T	IOContainer.get(java.lang.Class<T> cls) Gets the first IOObject which is of class cls.
<T extends IOObject> T	IOContainer.get(java.lang.Class<T> cls, int nr) Gets the nr-th IOObject which is of class cls.
protected <T extends IOObject> T	Operator.getInput(java.lang.Class<T> cls) Returns an IOObject of class cls.
protected <T extends IOObject> T	Operator.getInput(java.lang.Class<T> cls, int nr) Returns the nr-th IOObject of class cls.
<T extends IOObject> T	IOContainer.remove(java.lang.Class<T> cls) Removes the first IOObject which is of class cls.
<T extends IOObject> T	IOContainer.remove(java.lang.Class<T> cls, int nr) Removes the nr-th IOObject which is of class cls.

Methods in com.rapidminer.operator that return IOObject

IOObject[]	SQLExecution.apply()
IOObject[]	SingleMacroDefinitionOperator.apply()
IOObject[]	ScriptingOperator.apply()
IOObject[]	OperatorChain.apply() Applies all inner operators.
abstract IOObject[]	Operator.apply() Implement this method in subclasses.
IOObject[]	ModelUpdater.apply() Applies the operator and labels the ExampleSet.
IOObject[]	ModelUngrouper.apply()
IOObject[]	ModelGrouper.apply()
IOObject[]	ModelApplier.apply() Applies the operator and labels the ExampleSet.
IOObject[]	MemoryCleanUp.apply()
IOObject[]	MacroDefinitionOperator.apply()
IOObject[]	MacroConstructionOperator.apply()
IOObject[]	IOStorageOperator.apply()
IOObject[]	IOSelectOperator.apply()
IOObject[]	IORetrievalOperator.apply()
IOObject[]	IOMultiplyOperator.apply()
IOObject[]	IOConsumeOperator.apply()
IOObject[]	FileEchoOperator.apply()
IOObject[]	DataMacroDefinitionOperator.apply()
IOObject[]	CommandLineOperator.apply()
IOObject[]	AbstractExampleSetProcessing.apply()
IOObject	IOObject.copy() Should return a copy of this IOObject.
IOObject	AbstractIOObject.copy() Returns not a copy but the very same object.
IOObject	IOContainer.getElementAt(int index) Returns the n-th IOObject in this container.
IOObject[]	IOContainer.getIOObjects() Returns all IOObjects.
static IOObject	AbstractIOObject.read(java.io.InputStream in) Deserializes an IOObect from the given XML stream.
IOObject	IOContainer.removeElementAt(int index) Removes and returns the n-th IOObject in this container.

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

IOContainer	IOContainer.append(IOObject object) Creates a new IOContainer by adding all IOObjects of this container to the given IOObject.
IOContainer	IOContainer.append(IOObject[] output) Creates a new IOContainer by adding all IOObjects of this container to the given IOObjects.
IOContainer	IOContainer.prepend(IOObject object) Creates a new IOContainer by adding the given object before the IOObjects of this container.
IOContainer	IOContainer.prepend(IOObject[] output) Creates a new IOContainer by adding the given objects before the IOObjects of this container.

Method parameters in com.rapidminer.operator with type arguments of type IOObject

IOContainer	IOContainer.append(java.util.Collection<IOObject> output) Appends this container's IOObjects to output.
boolean	IOContainer.contains(java.lang.Class<? extends IOObject> cls) Returns true if this IOContainer containts an IOObject of the desired class.
protected boolean	Operator.hasInput(java.lang.Class<? extends IOObject> cls) Returns true if this operator has an input object of the desired class.

Constructors in com.rapidminer.operator with parameters of type IOObject

IOContainer(IOObject... objectArray)

Constructor parameters in com.rapidminer.operator with type arguments of type IOObject

IOContainer(java.util.Collection<? extends IOObject> objectCollection)
Creates a new IOContainer containing the contents of the Collection which must contain only IOObjects.

Uses of IOObject in com.rapidminer.operator.clustering

Classes in com.rapidminer.operator.clustering that implement IOObject

class	CentroidClusterModel This is the superclass for all centroid based cluster models and supports assigning unseen examples to the nearest centroid.
class	ClusterModel This class is the standard flat cluster model, using the example ids to remember which examples were assigned to which cluster.
class	DendogramHierarchicalClusterModel This class only indicates that this model is providing information for plotting a dendogram.
class	FlatFuzzyClusterModel This class represents a stadard implementation of a flat, fuzzy clustering.
class	HierarchicalClusterModel This class provides the data of a generic hierarchical cluster model.
class	WekaClusterModel A Weka clusterer which can be used to cluster examples.

Methods in com.rapidminer.operator.clustering that return IOObject

IOObject[]	FlattenClusterModel.apply()
IOObject[]	ClusterToPrediction.apply()
IOObject[]	ClusterModel2ExampleSet.apply()

Uses of IOObject in com.rapidminer.operator.clustering.clusterer

Methods in com.rapidminer.operator.clustering.clusterer that return IOObject

IOObject[]	TopDownClustering.apply()
IOObject[]	ExampleSet2ClusterModel.apply()
IOObject[]	AgglomerativeClustering.apply()
IOObject[]	AbstractClusterer.apply()

Uses of IOObject in com.rapidminer.operator.features

Methods in com.rapidminer.operator.features that return IOObject

IOObject[]	FeatureOperator.apply() Applies the feature operator: collects the pre- and postevaluation operators create an initial population evaluate the initial population loop as long as solution is not good enough apply all pre evaluation operators evaluate the population update the population's best individual apply all post evaluation operators return all generation's best individual
IOObject[]	AttributeWeightsApplier.apply()

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

Methods in com.rapidminer.operator.features.aggregation that return IOObject

IOObject[]

EvolutionaryFeatureAggregation.apply()

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

Methods in com.rapidminer.operator.features.construction that return IOObject

IOObject[]	YAGGA2.apply()
IOObject[]	ExampleSetBasedFeatureOperator.apply() Applies the feature operator: collects the pre- and postevaluation operators create an initial population evaluate the initial population loop as long as solution is not good enough apply all pre evaluation operators evaluate the population update the population's best individual apply all post evaluation operators return all generation's best individual
IOObject[]	AGA.apply()

Uses of IOObject in com.rapidminer.operator.features.selection

Methods in com.rapidminer.operator.features.selection that return IOObject

IOObject[]	ForwardSelectionOperator.apply()
IOObject[]	FeatureSelectionOperator.apply()
IOObject[]	AttributeWeightSelection.apply()

Methods in com.rapidminer.operator.features.selection with parameters of type IOObject

IOContainer

ForwardSelectionOperator.applyInnerLearner(IOObject... objects)

Uses of IOObject in com.rapidminer.operator.features.transformation

Classes in com.rapidminer.operator.features.transformation that implement IOObject

class	DimensionalityReducerModel The model for the generic dimensionality reducer.
class	FastICAModel This is the transformation model of the FastICA.
class	GHAModel This is the transformation model of the GHA The number of components is initially specified by the GHA.
class	KernelPCAModel The model for the Kernel-PCA.
class	PCAModel This is the transformation model of the principal components analysis.
class	SOMDimensionalityReductionModel The model for the SOM dimensionality reduction.

Methods in com.rapidminer.operator.features.transformation that return IOObject

IOObject[]	SOMDimensionalityReduction.apply()
IOObject[]	PCA.apply()
IOObject[]	KernelPCA.apply()
IOObject[]	GHA.apply()
IOObject[]	FastICA.apply()
IOObject[]	DimensionalityReducer.apply()

Uses of IOObject in com.rapidminer.operator.features.weighting

Methods in com.rapidminer.operator.features.weighting that return IOObject

IOObject[]	PSOWeighting.apply()
IOObject[]	ProcessLog2AttributeWeights.apply()
IOObject[]	InteractiveAttributeWeighting.apply()
IOObject[]	FeatureWeighting.apply()
IOObject[]	ExampleSet2AttributeWeights.apply()
IOObject[]	ComponentWeights.apply()
IOObject[]	AttributeWeights2ExampleSet.apply()
IOObject[]	AbstractWeighting.apply()

Uses of IOObject in com.rapidminer.operator.io

Classes in com.rapidminer.operator.io with type parameters of type IOObject

class	AbstractReader<T extends IOObject> Superclass of all operators that have no input and generate a single output.
class	AbstractWriter<T extends IOObject> Superclass of all operators that take a single object as input, save it to disk and return the same object as output.

Methods in com.rapidminer.operator.io that return IOObject

IOObject[]	ResultWriter.apply() Use the ResultService to write the results of all input ResultObjects into the result file.
IOObject[]	IOObjectWriter.apply() Writes the attribute set to a file.
IOObject[]	IOObjectReader.apply() Writes the attribute set to a file.
IOObject[]	IOContainerWriter.apply()
IOObject[]	IOContainerReader.apply()
IOObject[]	GNUPlotOperator.apply()
IOObject[]	ClusterModelWriter.apply()
IOObject[]	AttributeConstructionsWriter.apply() Writes the attribute set to a file.
IOObject[]	AttributeConstructionsLoader.apply() Loads the attribute set from a file and constructs desired features.
IOObject[]	AbstractWriter.apply()
IOObject[]	AbstractReader.apply()
protected IOObject	IOObjectReader.read()

Uses of IOObject in com.rapidminer.operator.learner

Subinterfaces of IOObject in com.rapidminer.operator.learner

interface

FormulaProvider This interface indicates that the model is able to produce a human and machine readable formula which can then be parsed by other programs and used for predictions.

Classes in com.rapidminer.operator.learner that implement IOObject

class	PredictionModel PredictionModel is the superclass for all objects generated by learners, i.e.
class	SimpleBinaryPredictionModel A model that can be applied to an example set by applying it to each example separately.
class	SimplePredictionModel A model that can be applied to an example set by applying it to each example separately.

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

IOObject[]

AbstractLearner.apply() Trains a model using an ExampleSet from the input.

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

Classes in com.rapidminer.operator.learner.associations that implement IOObject

class	AssociationRules A set of AssociationRules which can be constructed from frequent item sets.
class	FrequentItemSets Contains a collection of FrequentItemSets.

Methods in com.rapidminer.operator.learner.associations that return IOObject

IOObject[]	FrequentItemSetUnificator.apply()
IOObject[]	FrequentItemSetAttributeCreator.apply()
IOObject[]	AssociationRuleGenerator.apply()

Uses of IOObject in com.rapidminer.operator.learner.associations.fpgrowth

Methods in com.rapidminer.operator.learner.associations.fpgrowth that return IOObject

IOObject[]

FPGrowth.apply()

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

Classes in com.rapidminer.operator.learner.bayes that implement IOObject

class	DiscriminantModel This is the model for discriminant analysis based learning schemes.
class	DistributionModel DistributionModel is a model for learners which estimate distributions of attribute values from example sets like NaiveBayes.
class	KernelDistributionModel KernelDistributionModel is a model for learners which estimate distributions of attribute values from example sets like NaiveBayes.
class	SimpleDistributionModel DistributionModel is a model for learners which estimate distributions of attribute values from example sets like NaiveBayes.

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

Classes in com.rapidminer.operator.learner.functions that implement IOObject

class	FastMarginModel This is the model of the fast margin learner which learns a linear SVM in linear time.
class	HyperplaneModel This model is a separating hyperplane for two classes.
class	LinearRegressionModel The model for linear regression.
class	LogisticRegressionModel The model determined by the LogisticRegression operator.
class	PolynomialRegressionModel The model for the polynomial regression.
class	VectorRegressionModel The model for vector linear regression.

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

Classes in com.rapidminer.operator.learner.functions.kernel that implement IOObject

class	AbstractMySVMModel The abstract superclass for the SVM models by Stefan Rueping.
class	GPModel A model learned by the GPLearner.
class	JMySVMModel The implementation for the mySVM model (Java version) by Stefan Rueping.
class	KernelLogisticRegressionModel The model determined by the KernelLogisticRegression operator.
class	KernelModel This is the abstract model class for all kernel models.
class	LibSVMModel A model generated by the libsvm by Chih-Chung Chang and Chih-Jen Lin.
class	MyKLRModel The model for the MyKLR learner by Stefan Rueping.
class	RVMModel A model generated by the RVMLearner.

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

Classes in com.rapidminer.operator.learner.functions.kernel.evosvm that implement IOObject

class

EvoSVMModel The model for the evolutionary SVM.

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

Classes in com.rapidminer.operator.learner.functions.kernel.hyperhyper that implement IOObject

class

HyperModel The model for the HyperHyper implementation.

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

Classes in com.rapidminer.operator.learner.functions.neuralnet that implement IOObject

class	ImprovedNeuralNetModel The model of the improved neural net.
class	NeuralNetModel This is the model for the neural net learner.
class	SimpleNeuralNetModel This is the model for the simple neural net learner.

Uses of IOObject in com.rapidminer.operator.learner.igss

Classes in com.rapidminer.operator.learner.igss that implement IOObject

class

IGSSResult This class stores all results found by the IGSS algorithm.

Methods in com.rapidminer.operator.learner.igss that return IOObject

IOObject[]

IteratingGSS.apply()

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

Classes in com.rapidminer.operator.learner.igss.hypothesis that implement IOObject

class

GSSModel Wrapper class for rules found by the Iterating GSS algorithm.

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

Classes in com.rapidminer.operator.learner.lazy that implement IOObject

class	AttributeBasedVotingModel Average model simply calculates the average of the attributes as prediction.
class	DefaultModel The default model sets the prediction of all examples to the mode value in case of nominal labels and to the average value in case of numerical labels.
class	KNNClassificationModel An implementation of a knn model.
class	KNNRegressionModel An implementation of a knn model used for regression

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

Classes in com.rapidminer.operator.learner.meta that implement IOObject

class	AdaBoostModel A model for the RapidMiner AdaBoost implementation.
class	AdditiveRegressionModel The model created by an AdditiveRegression meta learner.
class	BaggingModel The model for the internal Bagging implementation.
class	BayBoostModel A model for the Bayesian Boosting algorithm by Martin Scholz.
class	Binary2MultiClassModel This operator uses an inner learning scheme which is able to perform predictions for binary or binominal classification problems and learns a set of these binary models in order to use this set for a given data set with more than two classes.
class	MetaCostModel This class is associated to the MetaCost operator and supports the evaluation procedures of the MetaCost method.
class	MultiModel MultiModels are used for multi class learning tasks.
class	MultiModelByRegression MultiModels are used for multi class learning tasks.
class	RelativeRegressionModel The model for the relative regression meta learner.
class	SDEnsemble A subgroup discovery model.
class	SimpleVoteModel A simple vote model.
class	StackingModel This class is the model build by the Stacking operator.
class	ThresholdModel This model is created by the CostBasedThresholdLearner.
class	TransformedRegressionModel Model for TransformedRegression.

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

IOObject[]	TransformedRegression.apply()
IOObject[]	SDRulesetInduction.apply() Constructs a Model repeatedly running a weak learner, reweighting the training example set accordingly, and combining the hypothesis using the available weighted performance values.
IOObject[]	BayBoostStream.apply() Overwrite to also return the performance (run-) vector
IOObject[]	AbstractMetaLearner.apply() Trains a model using an ExampleSet from the input.

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

Classes in com.rapidminer.operator.learner.rules that implement IOObject

class	ConjunctiveRuleModel Each object of this class represents a conjunctive rule with boolean target and nominal attributes.
class	RuleModel The basic rule model.

Uses of IOObject in com.rapidminer.operator.learner.subgroups

Classes in com.rapidminer.operator.learner.subgroups that implement IOObject

class

RuleSet A model consisting of rules which are scored by utility values.

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

Classes in com.rapidminer.operator.learner.tree that implement IOObject

static class	MultiCriterionDecisionStumps.DecisionStumpModel
class	TreeModel The tree model is the model created by all decision trees.

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

Classes in com.rapidminer.operator.learner.weka that implement IOObject

class	WekaAssociator In contrast to models generated by normal learners, the association rules cannot be applied to an example set.
class	WekaClassifier A Weka Classifier which can be used to classify Examples.

Methods in com.rapidminer.operator.learner.weka that return IOObject

IOObject[]	GenericWekaMetaLearner.apply()
IOObject[]	GenericWekaEnsembleLearner.apply()
IOObject[]	GenericWekaAssociationLearner.apply()

Uses of IOObject in com.rapidminer.operator.meta

Classes in com.rapidminer.operator.meta that implement IOObject

class

ParameterSet A set of parameters generated by a ParameterOptimizationOperator.

Methods in com.rapidminer.operator.meta that return IOObject

IOObject[]	XVPrediction.apply()
IOObject[]	WeightOptimization.apply()
IOObject[]	ValueSubgroupIteration.apply()
IOObject[]	ValueIteration.apply()
IOObject[]	UnivariateLabelSeriesPrediction.apply()
IOObject[]	RepeatUntilOperatorChain.apply()
IOObject[]	RandomOptimizationChain.apply()
IOObject[]	QuadraticParameterOptimizationOperator.apply()
IOObject[]	ProcessEmbeddingOperator.apply()
IOObject[]	PartialExampleSetLearner.apply()
IOObject[]	ParameterSetter.apply()
IOObject[]	ParameterIteration.apply()
IOObject[]	ParameterCloner.apply()
IOObject[]	OperatorSelector.apply()
IOObject[]	OperatorEnabler.apply()
IOObject[]	MultipleLabelIterator.apply()
IOObject[]	LearningCurveOperator.apply()
IOObject[]	IterativeWeightOptimization.apply()
IOObject[]	IteratingOperatorChain.apply()
IOObject[]	GridSearchParameterOptimizationOperator.apply()
IOObject[]	FileIterator.apply()
IOObject[]	FeatureSubsetIteration.apply()
IOObject[]	FeatureIterator.apply()
IOObject[]	ExceptionHandling.apply()
IOObject[]	ExampleSetIterator.apply()
IOObject[]	EvolutionaryParameterOptimizationOperator.apply()
IOObject[]	ClusterIterator.apply()
IOObject[]	BatchProcessing.apply()
IOObject[]	AverageBuilder.apply()
IOObject[]	AbstractSplitChain.apply()

Uses of IOObject in com.rapidminer.operator.meta.branch

Methods in com.rapidminer.operator.meta.branch with type parameters of type IOObject

<T extends IOObject> T

ProcessBranch.getConditionInput(java.lang.Class<T> cls)

Methods in com.rapidminer.operator.meta.branch that return IOObject

IOObject[]

ProcessBranch.apply()

Methods in com.rapidminer.operator.meta.branch that return types with arguments of type IOObject

java.lang.Class<IOObject>

ProcessBranch.getSelectedClass()

Uses of IOObject in com.rapidminer.operator.performance

Classes in com.rapidminer.operator.performance that implement IOObject

class	AbsoluteError The absolute error: Sum(|label-predicted|)/#examples.
class	AreaUnderCurve This criterion calculates the area under the ROC curve.
class	BinaryClassificationPerformance This class encapsulates the well known binary classification criteria precision and recall.
class	CorrelationCriterion Computes the empirical corelation coefficient 'r' between label and prediction.
class	CrossEntropy Calculates the cross-entropy for the predictions of a classifier.
class	EstimatedPerformance This class is used to store estimated performance values before or even without the performance test is actually done using a test set.
class	LenientRelativeError The average relative error in a lenient way of calculation: Sum(|label-predicted|/max(|label|, |predicted|))/#examples.
class	LogisticLoss The logistic loss of a classifier, defined as the average over all ln(1 + exp(-y * f(x)))
class	Margin The margin of a classifier, defined as the minimal confidence for the correct label.
class	MDLCriterion Measures the length of an example set (i.e. the number of attributes).
class	MeasuredPerformance Superclass for performance citeria that are actually measured (not estimated).
class	MinMaxCriterion This criterion should be used as wrapper around other performance criteria (see MinMaxWrapper).
class	MultiClassificationPerformance Measures the accuracy and classification error for both binary classification problems and multi class problems.
class	NormalizedAbsoluteError Normalized absolute error is the total absolute error normalized by the error simply predicting the average of the actual values.
class	PerformanceCriterion Each PerformanceCriterion contains a method to compute this criterion on a given set of examples, each which has to have a real and a predicted label.
class	PerformanceVector Handles several performance criteria.
class	PredictionAverage Returns the average value of the prediction.
class	PredictionTrendAccuracy Measures the number of times a regression prediction correctly determines the trend.
class	RankCorrelation Computes either the Spearman (rho) or Kendall (tau-b) rank correlation between the actual label and predicted values of an example set.
class	RelativeError The average relative error: Sum(|label-predicted|/label)/#examples.
class	RootMeanSquaredError The root-mean-squared error.
class	RootRelativeSquaredError Relative squared error is the total squared error made relative to what the error would have been if the prediction had been the average of the absolute value.
class	SimpleClassificationError This class calculates the classification error without determining the complete contingency table.
class	SimpleCriterion Simple criteria are those which error can be counted for each example and can be averaged by the number of examples.
class	SoftMarginLoss The soft margin loss of a classifier, defined as the average over all 1 - y * f(x).
class	SquaredCorrelationCriterion Computes the square of the empirical corellation coefficient 'r' between label and prediction.
class	SquaredError The squared error.
class	StrictRelativeError The average relative error in a strict way of calculation: Sum(|label-predicted|/min(|label|, |predicted|))/#examples.
class	WeightedMultiClassPerformance Measures the weighted mean of all per class recalls or per class precisions based on the weights defined in the performance evaluator.

Methods in com.rapidminer.operator.performance that return IOObject

IOObject[]	WeightedPerformanceCreator.apply()
IOObject[]	SupportVectorCounter.apply()
IOObject[]	MinMaxWrapper.apply()
IOObject[]	AbstractPerformanceEvaluator.apply()
IOObject[]	AbstractExampleSetEvaluator.apply()

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

Classes in com.rapidminer.operator.performance.cost that implement IOObject

class

ClassificationCostCriterion This performance Criterion works with a given cost matrix.

Methods in com.rapidminer.operator.performance.cost that return IOObject

IOObject[]

CostEvaluator.apply()

Uses of IOObject in com.rapidminer.operator.postprocessing

Classes in com.rapidminer.operator.postprocessing that implement IOObject

class	PlattScalingModel A model that contains a boolean classifier and a scaling operation that turns confidence scores into probability estimates.
class	Threshold A threshold for soft2crisp classifying.

Methods in com.rapidminer.operator.postprocessing that return IOObject

IOObject[]	ThresholdFinder.apply()
IOObject[]	ThresholdCreator.apply()
IOObject[]	ThresholdApplier.apply()
IOObject[]	PlattScaling.apply()

Uses of IOObject in com.rapidminer.operator.preprocessing

Classes in com.rapidminer.operator.preprocessing that implement IOObject

class

PreprocessingModel Returns a more appropriate result icon.

Methods in com.rapidminer.operator.preprocessing that return IOObject

IOObject[]	PreprocessingOperator.apply()
IOObject[]	GroupByOperator.apply()
IOObject[]	AttributeSubsetPreprocessing.apply()

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

Classes in com.rapidminer.operator.preprocessing.discretization that implement IOObject

class

DiscretizationModel The generic discretization model.

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

Classes in com.rapidminer.operator.preprocessing.filter that implement IOObject

class	Dictionary Replaces strings
class	NominalToBinominalModel This model maps the values of all nominal values to binary attributes.

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

IOObject[]	NonDominatedSorting.apply()
IOObject[]	MissingValueImputation.apply()

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

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

IOObject[]	ExampleSetUnion.apply()
IOObject[]	ExampleSetSuperset.apply()
IOObject[]	ExampleSetMinus.apply()
IOObject[]	ExampleSetMerge.apply()
IOObject[]	ExampleSetIntersect.apply()
IOObject[]	AbstractExampleSetJoin.apply()

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

Classes in com.rapidminer.operator.preprocessing.normalization that implement IOObject

class	MinMaxNormalizationModel A simple model which can be used to transform all regular attributes into a value range between the given min and max values.
class	ProportionNormalizationModel This model is able to transform the data in a way, every transformed attribute of an example contains the proportion of the total sum of this attribute over all examples.
class	ZTransformationModel This model performs a z-Transformation on the given example set.

Uses of IOObject in com.rapidminer.operator.preprocessing.sampling

Methods in com.rapidminer.operator.preprocessing.sampling that return IOObject

IOObject[]

PartitionOperator.apply()

Uses of IOObject in com.rapidminer.operator.preprocessing.series.filter

Methods in com.rapidminer.operator.preprocessing.series.filter that return IOObject

IOObject[]	Trend.apply()
IOObject[]	LagSeries.apply()

Uses of IOObject in com.rapidminer.operator.preprocessing.transformation

Methods in com.rapidminer.operator.preprocessing.transformation that return IOObject

IOObject[]	GroupedANOVAOperator.apply()
IOObject[]	Example2AttributePivoting.apply()
IOObject[]	Attribute2ExamplePivoting.apply()

Uses of IOObject in com.rapidminer.operator.similarity

Classes in com.rapidminer.operator.similarity that implement IOObject

class

SimilarityMeasure This is a wrapper around a DistanceMeasure.

Methods in com.rapidminer.operator.similarity that return IOObject

IOObject[]	Similarity2ExampleSet.apply()
IOObject[]	ExampleSet2SimilarityExampleSet.apply()
IOObject[]	ExampleSet2Similarity.apply()

Uses of IOObject in com.rapidminer.operator.text

Classes in com.rapidminer.operator.text that implement IOObject

class

TextObject This object encapsulates arbitrary text together with a label if applicable.

Methods in com.rapidminer.operator.text that return IOObject

IOObject[]	TextSegmenter.apply()
IOObject[]	TextObjectWriter.apply()
IOObject[]	TextObjectLoader.apply()
IOObject[]	TextObject2ExampleSet.apply()
IOObject[]	TextExtractor.apply()
IOObject[]	TextCleaner.apply()
IOObject[]	SingleTextObjectInput.apply()

Uses of IOObject in com.rapidminer.operator.validation

Methods in com.rapidminer.operator.validation that return IOObject

IOObject[]	WrapperXValidation.apply()
IOObject[]	ValidationChain.apply()
IOObject[]	RandomSplitWrapperValidationChain.apply()
IOObject[]	IteratingPerformanceAverage.apply()
IOObject[]	XValidation.estimatePerformance(ExampleSet inputSet)
abstract IOObject[]	ValidationChain.estimatePerformance(ExampleSet inputSet) This is the main method of the validation chain and must be implemented to estimate a performance of inner operators on the given example set.
IOObject[]	SlidingWindowValidation.estimatePerformance(ExampleSet inputSet)
IOObject[]	RandomSplitValidationChain.estimatePerformance(ExampleSet inputSet)
IOObject[]	FixedSplitValidationChain.estimatePerformance(ExampleSet inputSet)
IOObject[]	BatchXValidation.estimatePerformance(ExampleSet inputSet)
IOObject[]	BatchSlidingWindowValidation.estimatePerformance(ExampleSet inputSet)
IOObject[]	AbstractBootstrappingValidation.estimatePerformance(ExampleSet inputSet)

Uses of IOObject in com.rapidminer.operator.validation.clustering

Methods in com.rapidminer.operator.validation.clustering that return IOObject

IOObject[]	TestEvaluator.apply()
IOObject[]	ClusterNumberEvaluator.apply()
IOObject[]	ClusterDensityEvaluator.apply()
IOObject[]	CentroidBasedEvaluator.apply()

Uses of IOObject in com.rapidminer.operator.validation.clustering.exampledistribution

Methods in com.rapidminer.operator.validation.clustering.exampledistribution that return IOObject

IOObject[]

ExampleDistributionEvaluator.apply()

Uses of IOObject in com.rapidminer.operator.validation.significance

Classes in com.rapidminer.operator.validation.significance that implement IOObject

static class

TTestSignificanceTestOperator.TTestSignificanceTestResult The result for a paired t-test.

Methods in com.rapidminer.operator.validation.significance that return IOObject

IOObject[]

SignificanceTestOperator.apply() Writes the attribute set to a file.

Uses of IOObject in com.rapidminer.operator.visualization

Classes in com.rapidminer.operator.visualization that implement IOObject

class	DataStatistics This class encapsulates some very simple statistics about the given attributes.
class	LiftParetoChart This object can usually not be passed to other operators but can simply be used for the inline visualization of a Lift Pareto chart (without a dialog).
class	ROCComparison This object can usually not be passed to other operators but can simply be used for the inline visualization of a ROC comparison plot (without a dialog).

Methods in com.rapidminer.operator.visualization that return IOObject

IOObject[]	SOMModelVisualization.apply()
IOObject[]	ROCChartGenerator.apply()
IOObject[]	ROCBasedComparisonOperator.apply()
IOObject[]	ProcessLogOperator.apply()
IOObject[]	ProcessLog2ExampleSet.apply()
IOObject[]	Macro2Log.apply()
IOObject[]	LiftParetoChartGenerator.apply()
IOObject[]	LiftChartGenerator.apply()
IOObject[]	FormulaExtractor.apply()
IOObject[]	ExampleVisualizationOperator.apply()
IOObject[]	DataStatisticsOperator.apply() Creates and delivers the simple statistics object.
IOObject[]	DatabaseExampleVisualizationOperator.apply()
IOObject[]	Data2Log.apply()
IOObject[]	ClearProcessLog.apply()

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

Classes in com.rapidminer.operator.visualization.dependencies that implement IOObject

class	ANOVAMatrix Displays the result of an ANOVA matrix calculation.
class	NumericalMatrix A simple (symmetrical) matrix which can be used for correlation or covariance matrices.
class	RainflowMatrix The Rainflow Matrix adds another data table view for the residuals of the Rainflow Matrix calculation as well as a new plot tab for the residuals.
class	TransitionGraph This is the result of the TransitionGraphOperator, i.e. a graph representing connections between items (can be used for network visualizations).

Methods in com.rapidminer.operator.visualization.dependencies that return IOObject

IOObject[]	TransitionMatrixOperator.apply()
IOObject[]	TransitionGraphOperator.apply()
IOObject[]	RainflowMatrixOperator.apply()
IOObject[]	CovarianceMatrixOperator.apply()
IOObject[]	CorrelationMatrixOperator.apply()
IOObject[]	ANOVAMatrixOperator.apply()
IOObject[]	AbstractPairwiseMatrixOperator.apply()

Uses of IOObject in com.rapidminer.test

Constructor parameters in com.rapidminer.test with type arguments of type IOObject

IOObjectSampleTest(java.lang.String file, java.util.Collection<java.lang.Class<IOObject>> ioObjects)

Uses of IOObject in com.rapidminer.tools

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

static java.lang.Class<IOObject>

OperatorService.getIOObjectClass(java.lang.String name) Returns the class for the short name of an IO object.

Uses of IOObject in com.rapidminer.tools.math

Classes in com.rapidminer.tools.math that implement IOObject

static class	AnovaCalculator.AnovaSignificanceTestResult
class	Averagable Superclass for all objects which can be averaged.
class	AverageVector Handles several averagables.
class	RunVector Collects the average vectors of a run.
class	SignificanceTestResult This class encapsulates the result of a statistical significance test.