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#Weka.classifiers Classes and Interfaces - 170 results found.
NameDescriptionTypePackageFramework
AbstractClassifierAbstract classifier.Classweka.classifiersWeka
AbstractEvaluationMetricAbstract base class for pluggable classification/regression evaluationVersion:$Revision: 12409 $Author:Mark Hall (mhall{[at]}pentaho{[dot]}com)See Also:Serialized FormClassweka.classifiers.evaluationWeka
AbstractOutputA superclass for outputting the classifications of a classifier.Classweka.classifiers.evaluation.output.predictionWeka
AbstractPMMLProducerHelperAbstract base class for PMMLProducer helper classes to extend.Classweka.classifiers.pmml.producerWeka
ActiveHNodeNode that is "active" (i.Classweka.classifiers.trees.htWeka
AdaBoostM1 Class for boosting a nominal class classifier using the Adaboost M1 method.Classweka.classifiers.metaWeka
AdditiveRegression Meta classifier that enhances the performance of a regression base classifier.Classweka.classifiers.metaWeka
ADNodeThe ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set inClassweka.classifiers.bayes.netWeka
AggregateableEvaluationSubclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.Classweka.classifiersWeka
AggregateableEvaluationSubclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.Classweka.classifiers.evaluationWeka
AttributeSelectedClassifier Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.Classweka.classifiers.metaWeka
Bagging Class for bagging a classifier to reduce variance.Classweka.classifiers.metaWeka
BayesNet Bayes Network learning using various search algorithms and quality measures.Classweka.classifiers.bayesWeka
BayesNetEstimator BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure hasClassweka.classifiers.bayes.net.estimateWeka
BayesNetGenerator Bayes Network learning using various search algorithms and quality measures.Classweka.classifiers.bayes.netWeka
BIFReader Builds a description of a Bayes Net classifier stored in XML BIF 0.Classweka.classifiers.bayes.netWeka
BinC45ModelSelectionClass for selecting a C4.Classweka.classifiers.trees.j48Weka
BinC45SplitClass implementing a binary C4.Classweka.classifiers.trees.j48Weka
BMAEstimator BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA).Classweka.classifiers.bayes.net.estimateWeka
BVDecompose Class for performing a Bias-Variance decomposition on any classifier using the method specified in: Ron Kohavi, David H.Classweka.classifiersWeka
BVDecomposeSegCVSub This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1).Classweka.classifiersWeka
C45ModelSelectionClass for selecting a C4.Classweka.classifiers.trees.j48Weka
C45PruneableClassifierTreeClass for handling a tree structure that can be pruned using C4.Classweka.classifiers.trees.j48Weka
C45PruneableDecListClass for handling a partial tree structure pruned using C4.Classweka.classifiers.rules.partWeka
C45SplitClass implementing a C4.Classweka.classifiers.trees.j48Weka
CachedKernelBase class for RBFKernel and PolyKernel that implements a simple LRU.Classweka.classifiers.functions.supportVectorWeka
CheckClassifierClass for examining the capabilities and finding problems with classifiers.Classweka.classifiersWeka
CheckKernelClass for examining the capabilities and finding problems with kernels.Classweka.classifiers.functions.supportVectorWeka
CheckSourceA simple class for checking the source generated from Classifiers implementing the weka.Classweka.classifiersWeka
CISearchAlgorithm The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).Classweka.classifiers.bayes.net.search.ciWeka
ClassificationViaRegression Class for doing classification using regression methods.Classweka.classifiers.metaWeka
ClassifierClassifier interface.Interfaceweka.classifiersWeka
ClassifierDecListClass for handling a rule (partial tree) for a decision list.Classweka.classifiers.rules.partWeka
ClassifierSplitModelAbstract class for classification models that can be used recursively to split the data.Classweka.classifiers.trees.j48Weka
ClassifierTreeClass for handling a tree structure used for classification.Classweka.classifiers.trees.j48Weka
ConditionalDensityEstimatorInterface for numeric prediction schemes that can output conditionalVersion:$Revision: 8034 $Author:Eibe Frank (eibe@cs.Interfaceweka.classifiersWeka
ConditionalSufficientStatsRecords sufficient stats for an attributeVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
ConfusionMatrixCells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.Classweka.classifiers.evaluationWeka
CorrelationSplitInfoFinds split points using correlation.Classweka.classifiers.trees.m5Weka
CostCurveGenerates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.Classweka.classifiers.evaluationWeka
CostMatrixClass for storing and manipulating a misclassification cost matrix.Classweka.classifiersWeka
CostSensitiveClassifier A metaclassifier that makes its base classifier cost-sensitive.Classweka.classifiers.metaWeka
CSV Outputs the predictions as CSV.Classweka.classifiers.evaluation.output.predictionWeka
CVParameterSelection Class for performing parameter selection by cross-validation for any classifier.Classweka.classifiers.metaWeka
DecisionStump Class for building and using a decision stump.Classweka.classifiers.treesWeka
DecisionTable Class for building and using a simple decision table majority classifier.Classweka.classifiers.rulesWeka
DecisionTableHashKeyClass providing hash table keys for DecisionTableSee Also:Serialized FormClassweka.classifiers.rulesWeka
DiscreteEstimatorBayesSymbolic probability estimator based on symbol counts and a prior.Classweka.classifiers.bayes.net.estimateWeka
DiscreteEstimatorFullBayesSymbolic probability estimator based on symbol counts and a prior.Classweka.classifiers.bayes.net.estimateWeka
DistributionClass for handling a distribution of class values.Classweka.classifiers.trees.j48Weka
EditableBayesNet Bayes Network learning using various search algorithms and quality measures.Classweka.classifiers.bayes.netWeka
EntropyBasedSplitCritClassweka.classifiers.trees.j48Weka
ModelSelectionAbstract class for model selection criteria.Classweka.classifiers.trees.j48Weka
MultiClassClassifier A metaclassifier for handling multi-class datasets with 2-class classifiers.Classweka.classifiers.metaWeka
MultiClassClassifierUpdateable A metaclassifier for handling multi-class datasets with 2-class classifiers.Classweka.classifiers.metaWeka
MultilayerPerceptron A Classifier that uses backpropagation to classify This network can be built by hand, created by an algorithm or both.Classweka.classifiers.functionsWeka
MultiNomialBMAEstimator Multinomial BMA Estimator.Classweka.classifiers.bayes.net.estimateWeka
MultipleClassifiersCombinerAbstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.Classweka.classifiersWeka
MultiScheme Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data.Classweka.classifiers.metaWeka
NaiveBayes Class for a Naive Bayes classifier using estimator classes.Classweka.classifiers.bayesWeka
NaiveBayes The NaiveBayes class generates a fixed Bayes network structure with arrows from the class variable to each of the attribute variables.Classweka.classifiers.bayes.net.search.fixedWeka
NaiveBayesMultinomialText Multinomial naive bayes for text data.Classweka.classifiers.bayesWeka
NaiveBayesUpdateable Class for a Naive Bayes classifier using estimator classes.Classweka.classifiers.bayesWeka
NBNodeClassweka.classifiers.trees.htWeka
NBNodeAdaptive Bayes for predictionVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
NBTreeClassifierTreeClass for handling a naive bayes tree structure used for classification.Classweka.classifiers.trees.j48Weka
NBTreeModelSelectionClass for selecting a NB tree split.Classweka.classifiers.trees.j48Weka
NBTreeNoSplitClass implementing a "no-split"-split (leaf node) for naive bayesVersion:$Revision: 10531 $Author:Mark Hall (mhall@cs.Classweka.classifiers.trees.j48Weka
NBTreeSplitClass implementing a NBTree split on an attribute.Classweka.classifiers.trees.j48Weka
NeuralConnectionAbstract unit in a NeuralNetwork.Classweka.classifiers.functions.neuralWeka
NeuralMethodThis is an interface used to create classes that can be used by the neuralnode to perform all it's computations.Interfaceweka.classifiers.functions.neuralWeka
NeuralNetworkClass implementing import of PMML Neural Network model.Classweka.classifiers.pmml.consumerWeka
NeuralNodeThis class is used to represent a node in the neuralnet.Classweka.classifiers.functions.neuralWeka
NominalConditionalSufficientStatsMaintains sufficient stats for the distribution of a nominal attributeVersion:$Revision: 10432 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
NominalPredictionEncapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.Classweka.classifiers.evaluationWeka
NormalizedPolyKernel The normalized polynomial kernel.Classweka.classifiers.functions.supportVectorWeka
NoSplitClass implementing a "no-split"-split.Classweka.classifiers.trees.j48Weka
Null Suppresses all output.Classweka.classifiers.evaluation.output.predictionWeka
NumericPredictionEncapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value.Classweka.classifiers.evaluationWeka
OneR Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizingClassweka.classifiers.rulesWeka
ParallelIteratedSingleClassifierEnhancerAbstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.Classweka.classifiersWeka
ParallelMultipleClassifiersCombinerAbstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multipleClassweka.classifiersWeka
ParentSetHelper class for Bayes Network classifiers.Classweka.classifiers.bayes.netWeka
PART Class for generating a PART decision list.Classweka.classifiers.rulesWeka
PlainText Outputs the predictions in plain text.Classweka.classifiers.evaluation.output.predictionWeka
PMMLClassifierAbstract base class for all PMML classifiers.Classweka.classifiers.pmml.consumerWeka
PolyKernel The polynomial kernel : K(x, y) = ^p or K(x, y) = (+1)^pClassweka.classifiers.functions.supportVectorWeka
PrecomputedKernelMatrixKernel This kernel is based on a static kernel matrix that is read from a file.Classweka.classifiers.functions.supportVectorWeka
PreConstructedLinearModelThis class encapsulates a linear regression function.Classweka.classifiers.trees.m5Weka
PredictionEncapsulates a single evaluatable prediction: the predicted value plus the actual class value.Interfaceweka.classifiers.evaluationWeka
PruneableClassifierTreeClass for handling a tree structure that can be pruned using a pruning set.Classweka.classifiers.trees.j48Weka
PruneableDecListClass for handling a partial tree structure that can be pruned using aVersion:$Revision: 10153 $Author:Eibe Frank (eibe@cs.Classweka.classifiers.rules.partWeka
Puk The Pearson VII function-based universal kernel.Classweka.classifiers.functions.supportVectorWeka
RandomCommittee Class for building an ensemble of randomizable base classifiers.Classweka.classifiers.metaWeka
RandomForest Class for constructing a forest of random trees.Classweka.classifiers.treesWeka
RandomizableClassifierAbstract utility class for handling settings common to randomizableVersion:$Revision: 10141 $Author:Eibe Frank (eibe@cs.Classweka.classifiersWeka
RandomizableFilteredClassifier Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.Classweka.classifiers.metaWeka
RandomizableIteratedSingleClassifierEnhancerAbstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.Classweka.classifiersWeka
RandomizableMultipleClassifiersCombinerAbstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers basedClassweka.classifiersWeka
RandomizableParallelIteratedSingleClassifierEnhancerAbstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single baseClassweka.classifiersWeka
RandomizableParallelMultipleClassifiersCombinerAbstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multipleClassweka.classifiersWeka
RandomizableSingleClassifierEnhancerAbstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.Classweka.classifiersWeka
RandomSubSpace This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity.Classweka.classifiers.metaWeka
RandomTree Class for constructing a tree that considers K randomly chosen attributes at each node.Classweka.classifiers.treesWeka
RBFKernel The RBF kernel.Classweka.classifiers.functions.supportVectorWeka
RegOptimizerBase class implementation for learning algorithm of SMOreg Valid options are:Classweka.classifiers.functions.supportVectorWeka
RegressionClass implementing import of PMML Regression model.Classweka.classifiers.pmml.consumerWeka
RegressionAnalysisAnalyzes linear regression model by using the Student's t-test on each coefficient.Classweka.classifiers.evaluationWeka
RegressionByDiscretization A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized.Classweka.classifiers.metaWeka
RegSMO Implementation of SMO for support vector regression A.Classweka.classifiers.functions.supportVectorWeka
RegSMOImproved Learn SVM for regression using SMO with Shevade, Keerthi, et al.Classweka.classifiers.functions.supportVectorWeka
RepeatedHillClimber This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure andClassweka.classifiers.bayes.net.search.globalWeka
RepeatedHillClimber This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure andClassweka.classifiers.bayes.net.search.localWeka
REPTree Fast decision tree learner.Classweka.classifiers.treesWeka
ResidualModelSelectionHelper class for logistic model trees (weka.Classweka.classifiers.trees.lmtWeka
ResidualSplitHelper class for logistic model trees (weka.Classweka.classifiers.trees.lmtWeka
RuleAbstract class of generic ruleVersion:$Revision: 8034 $Author:Xin Xu (xx5@cs.Classweka.classifiers.rulesWeka
RuleGenerates a single m5 tree or ruleVersion:$Revision: 10169 $Author:Mark HallSee Also:Serialized FormClassweka.classifiers.trees.m5Weka
RuleNodeConstructs a node for use in an m5 tree or ruleVersion:$Revision: 10283 $Author:Mark Hall (mhall@cs.Classweka.classifiers.trees.m5Weka
RuleSetModelClass implementing import of PMML RuleSetModel.Classweka.classifiers.pmml.consumerWeka
RuleStatsThis class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives,Classweka.classifiers.rulesWeka
ScoreableInterface for allowing to score a classifierVersion:$Revision: 8034 $Author:Remco Bouckaert (rrb@xm.Interfaceweka.classifiers.bayes.net.search.localWeka
SearchAlgorithmThis is the base class for all search algorithms for learning Bayes networks.Classweka.classifiers.bayes.net.searchWeka
SerializedClassifier A wrapper around a serialized classifier model.Classweka.classifiers.miscWeka
SGD Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression, squared loss, Huber loss and epsilon-insensitive loss linear regression).Classweka.classifiers.functionsWeka
SGDText Implements stochastic gradient descent for learning a linear binary class SVM or binary class logistic regression on text data.Classweka.classifiers.functionsWeka
SGDText .CountClassweka.classifiers.functionsWeka
SigmoidUnitThis can be used by the neuralnode to perform all it's computations (as a sigmoid unit).Classweka.classifiers.functions.neuralWeka
SimpleEstimator SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has beenClassweka.classifiers.bayes.net.estimateWeka
SimpleLinearRegression Learns a simple linear regression model.Classweka.classifiers.functionsWeka
SimpleLinearRegressionStripped down version of SimpleLinearRegression.Classweka.classifiers.trees.lmtWeka
SimpleLogistic Classifier for building linear logistic regression models.Classweka.classifiers.functionsWeka
SimulatedAnnealing This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoringClassweka.classifiers.bayes.net.search.globalWeka
SimulatedAnnealing This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoringClassweka.classifiers.bayes.net.search.localWeka
SingleClassifierEnhancerAbstract utility class for handling settings common to meta classifiers that use a single base learner.Classweka.classifiersWeka
SMO Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier.Classweka.classifiers.functionsWeka
SMOreg SMOreg implements the support vector machine for regression.Classweka.classifiers.functionsWeka
SMOsetStores a set of integer of a given size.Classweka.classifiers.functions.supportVectorWeka
SourcableInterface for classifiers that can be converted to Java source.Interfaceweka.classifiersWeka
SplitBase class for different split typesVersion:$Revision: 10531 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
SplitCandidateEncapsulates a candidate splitVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
SplitCriterionAbstract class for computing splitting criteria with respect to distributions of class values.Classweka.classifiers.trees.j48Weka
SplitEvaluateInterface for objects that determine a split point on an attributeVersion:$Revision: 8034 $Author:Mark Hall (mhall@cs.Interfaceweka.classifiers.trees.m5Weka
SplitMetricBase class for split metricsVersion:$Revision: 9720 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
SplitNodeClass for a node that splits the data in a Hoeffding treeVersion:$Revision: 10169 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
Stacking Combines several classifiers using the stacking method.Classweka.classifiers.metaWeka
StandardEvaluationMetricPrimarily a marker interface for a "standard" evaluation metric - i.Interfaceweka.classifiers.evaluationWeka
StatsClass implementing a statistical routine needed by J48 to compute its error estimate.Classweka.classifiers.trees.j48Weka
SupportVectorMachineModelClassweka.classifiers.pmml.consumerWeka
TabuSearch This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.Classweka.classifiers.bayes.net.search.globalWeka
TabuSearch This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.Classweka.classifiers.bayes.net.search.localWeka
TAN This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmentedClassweka.classifiers.bayes.net.search.globalWeka
TAN This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmentedClassweka.classifiers.bayes.net.search.localWeka
ThresholdCurveGenerates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes.Classweka.classifiers.evaluationWeka
ThresholdProducingMetricSome evaluation measures may optimize thresholds on the class probabilities.Interfaceweka.classifiers.evaluationWeka
TreeModelClass implementing import of PMML TreeModel.Classweka.classifiers.pmml.consumerWeka
TwoClassStatsEncapsulates performance functions for two-class problems.Classweka.classifiers.evaluationWeka
UnivariateNominalMultiwaySplitA multiway split based on a single nominal attributeVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
UnivariateNumericBinarySplitA binary split based on a single numeric attributeVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs.Classweka.classifiers.trees.htWeka
UpdateableBatchProcessorUpdateable classifiers can implement this if they wish to be informed at the end of the training stream.Interfaceweka.classifiersWeka
UpdateableClassifierInterface to incremental classification models that can learn using one instance at a time.Interfaceweka.classifiersWeka
ValuesStores some statistics.Classweka.classifiers.trees.m5Weka
VaryNodePart of ADTree implementation.Classweka.classifiers.bayes.netWeka
Vote Class for combining classifiers.Classweka.classifiers.metaWeka
VotedPerceptron Implementation of the voted perceptron algorithm by Freund and Schapire.Classweka.classifiers.functionsWeka
WeightedInstancesHandlerWrapper Generic wrapper around any classifier to enable weighted instances support.Classweka.classifiers.metaWeka
WeightMassSimple container for a weightVersion:$Revision: 9707 $Author:Mark Hall (mhall{[at]}pentaho{[dot]}com)See Also:Serialized FormClassweka.classifiers.trees.htWeka
XMLClassifierThis class serializes and deserializes a Classifier instance to andVersion:$Revision: 8034 $Author:FracPete (fracpete at waikato dot ac dot nz)Classweka.classifiers.xmlWeka
YongSplitInfoStores split information.Classweka.classifiers.trees.m5Weka
ZeroR Class for building and using a 0-R classifier.Classweka.classifiers.rulesWeka