Name | Description | Type | Package | Framework |
AbstractClassifier | Abstract classifier. | Class | weka.classifiers | Weka |
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AbstractEvaluationMetric | Abstract base class for pluggable classification/regression evaluationVersion:$Revision: 12409 $Author:Mark Hall (mhall{[at]}pentaho{[dot]}com)See Also:Serialized Form | Class | weka.classifiers.evaluation | Weka |
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AbstractOutput | A superclass for outputting the classifications of a classifier. | Class | weka.classifiers.evaluation.output.prediction | Weka |
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AbstractPMMLProducerHelper | Abstract base class for PMMLProducer helper classes to extend. | Class | weka.classifiers.pmml.producer | Weka |
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ActiveHNode | Node that is "active" (i. | Class | weka.classifiers.trees.ht | Weka |
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AdaBoostM1 | Class for boosting a nominal class classifier using the Adaboost M1 method. | Class | weka.classifiers.meta | Weka |
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AdditiveRegression | Meta classifier that enhances the performance of a regression base classifier. | Class | weka.classifiers.meta | Weka |
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ADNode | The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in | Class | weka.classifiers.bayes.net | Weka |
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AggregateableEvaluation | Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object. | Class | weka.classifiers | Weka |
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AggregateableEvaluation | Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object. | Class | weka.classifiers.evaluation | Weka |
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AttributeSelectedClassifier | Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier. | Class | weka.classifiers.meta | Weka |
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Bagging | Class for bagging a classifier to reduce variance. | Class | weka.classifiers.meta | Weka |
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BayesNet | Bayes Network learning using various search algorithms and quality measures. | Class | weka.classifiers.bayes | Weka |
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BayesNetEstimator | BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has | Class | weka.classifiers.bayes.net.estimate | Weka |
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BayesNetGenerator | Bayes Network learning using various search algorithms and quality measures. | Class | weka.classifiers.bayes.net | Weka |
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BIFReader | Builds a description of a Bayes Net classifier stored in XML BIF 0. | Class | weka.classifiers.bayes.net | Weka |
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BinC45ModelSelection | Class for selecting a C4. | Class | weka.classifiers.trees.j48 | Weka |
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BinC45Split | Class implementing a binary C4. | Class | weka.classifiers.trees.j48 | Weka |
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BMAEstimator | BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA). | Class | weka.classifiers.bayes.net.estimate | Weka |
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BVDecompose | Class for performing a Bias-Variance decomposition on any classifier using the method specified in: Ron Kohavi, David H. | Class | weka.classifiers | Weka |
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BVDecomposeSegCVSub | This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1). | Class | weka.classifiers | Weka |
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C45ModelSelection | Class for selecting a C4. | Class | weka.classifiers.trees.j48 | Weka |
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C45PruneableClassifierTree | Class for handling a tree structure that can be pruned using C4. | Class | weka.classifiers.trees.j48 | Weka |
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C45PruneableDecList | Class for handling a partial tree structure pruned using C4. | Class | weka.classifiers.rules.part | Weka |
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C45Split | Class implementing a C4. | Class | weka.classifiers.trees.j48 | Weka |
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CachedKernel | Base class for RBFKernel and PolyKernel that implements a simple LRU. | Class | weka.classifiers.functions.supportVector | Weka |
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CheckClassifier | Class for examining the capabilities and finding problems with classifiers. | Class | weka.classifiers | Weka |
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CheckKernel | Class for examining the capabilities and finding problems with kernels. | Class | weka.classifiers.functions.supportVector | Weka |
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CheckSource | A simple class for checking the source generated from Classifiers implementing the weka. | Class | weka.classifiers | Weka |
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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). | Class | weka.classifiers.bayes.net.search.ci | Weka |
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ClassificationViaRegression | Class for doing classification using regression methods. | Class | weka.classifiers.meta | Weka |
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Classifier | Classifier interface. | Interface | weka.classifiers | Weka |
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ClassifierDecList | Class for handling a rule (partial tree) for a decision list. | Class | weka.classifiers.rules.part | Weka |
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ClassifierSplitModel | Abstract class for classification models that can be used recursively to split the data. | Class | weka.classifiers.trees.j48 | Weka |
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ClassifierTree | Class for handling a tree structure used for classification. | Class | weka.classifiers.trees.j48 | Weka |
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ConditionalDensityEstimator | Interface for numeric prediction schemes that can output conditionalVersion:$Revision: 8034 $Author:Eibe Frank (eibe@cs. | Interface | weka.classifiers | Weka |
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ConditionalSufficientStats | Records sufficient stats for an attributeVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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ConfusionMatrix | Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination. | Class | weka.classifiers.evaluation | Weka |
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CorrelationSplitInfo | Finds split points using correlation. | Class | weka.classifiers.trees.m5 | Weka |
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CostCurve | Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes. | Class | weka.classifiers.evaluation | Weka |
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CostMatrix | Class for storing and manipulating a misclassification cost matrix. | Class | weka.classifiers | Weka |
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CostSensitiveClassifier | A metaclassifier that makes its base classifier cost-sensitive. | Class | weka.classifiers.meta | Weka |
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CSV | Outputs the predictions as CSV. | Class | weka.classifiers.evaluation.output.prediction | Weka |
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CVParameterSelection | Class for performing parameter selection by cross-validation for any classifier. | Class | weka.classifiers.meta | Weka |
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DecisionStump | Class for building and using a decision stump. | Class | weka.classifiers.trees | Weka |
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DecisionTable | Class for building and using a simple decision table majority classifier. | Class | weka.classifiers.rules | Weka |
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DecisionTableHashKey | Class providing hash table keys for DecisionTableSee Also:Serialized Form | Class | weka.classifiers.rules | Weka |
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DiscreteEstimatorBayes | Symbolic probability estimator based on symbol counts and a prior. | Class | weka.classifiers.bayes.net.estimate | Weka |
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DiscreteEstimatorFullBayes | Symbolic probability estimator based on symbol counts and a prior. | Class | weka.classifiers.bayes.net.estimate | Weka |
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Distribution | Class for handling a distribution of class values. | Class | weka.classifiers.trees.j48 | Weka |
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EditableBayesNet | Bayes Network learning using various search algorithms and quality measures. | Class | weka.classifiers.bayes.net | Weka |
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EntropyBasedSplitCrit | | Class | weka.classifiers.trees.j48 | Weka |
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ModelSelection | Abstract class for model selection criteria. | Class | weka.classifiers.trees.j48 | Weka |
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MultiClassClassifier | A metaclassifier for handling multi-class datasets with 2-class classifiers. | Class | weka.classifiers.meta | Weka |
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MultiClassClassifierUpdateable | A metaclassifier for handling multi-class datasets with 2-class classifiers. | Class | weka.classifiers.meta | Weka |
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MultilayerPerceptron | A Classifier that uses backpropagation to classify This network can be built by hand, created by an algorithm or both. | Class | weka.classifiers.functions | Weka |
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MultiNomialBMAEstimator | Multinomial BMA Estimator. | Class | weka.classifiers.bayes.net.estimate | Weka |
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MultipleClassifiersCombiner | Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers. | Class | weka.classifiers | Weka |
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MultiScheme | Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data. | Class | weka.classifiers.meta | Weka |
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NaiveBayes | Class for a Naive Bayes classifier using estimator classes. | Class | weka.classifiers.bayes | Weka |
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NaiveBayes | The NaiveBayes class generates a fixed Bayes network structure with arrows from the class variable to each of the attribute variables. | Class | weka.classifiers.bayes.net.search.fixed | Weka |
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NaiveBayesMultinomialText | Multinomial naive bayes for text data. | Class | weka.classifiers.bayes | Weka |
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NaiveBayesUpdateable | Class for a Naive Bayes classifier using estimator classes. | Class | weka.classifiers.bayes | Weka |
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NBNode | | Class | weka.classifiers.trees.ht | Weka |
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NBNodeAdaptive | Bayes for predictionVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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NBTreeClassifierTree | Class for handling a naive bayes tree structure used for classification. | Class | weka.classifiers.trees.j48 | Weka |
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NBTreeModelSelection | Class for selecting a NB tree split. | Class | weka.classifiers.trees.j48 | Weka |
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NBTreeNoSplit | Class implementing a "no-split"-split (leaf node) for naive bayesVersion:$Revision: 10531 $Author:Mark Hall (mhall@cs. | Class | weka.classifiers.trees.j48 | Weka |
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NBTreeSplit | Class implementing a NBTree split on an attribute. | Class | weka.classifiers.trees.j48 | Weka |
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NeuralConnection | Abstract unit in a NeuralNetwork. | Class | weka.classifiers.functions.neural | Weka |
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NeuralMethod | This is an interface used to create classes that can be used by the neuralnode to perform all it's computations. | Interface | weka.classifiers.functions.neural | Weka |
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NeuralNetwork | Class implementing import of PMML Neural Network model. | Class | weka.classifiers.pmml.consumer | Weka |
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NeuralNode | This class is used to represent a node in the neuralnet. | Class | weka.classifiers.functions.neural | Weka |
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NominalConditionalSufficientStats | Maintains sufficient stats for the distribution of a nominal attributeVersion:$Revision: 10432 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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NominalPrediction | Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value. | Class | weka.classifiers.evaluation | Weka |
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NormalizedPolyKernel | The normalized polynomial kernel. | Class | weka.classifiers.functions.supportVector | Weka |
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NoSplit | Class implementing a "no-split"-split. | Class | weka.classifiers.trees.j48 | Weka |
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Null | Suppresses all output. | Class | weka.classifiers.evaluation.output.prediction | Weka |
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NumericPrediction | Encapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value. | Class | weka.classifiers.evaluation | Weka |
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OneR | Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing | Class | weka.classifiers.rules | Weka |
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ParallelIteratedSingleClassifierEnhancer | Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner. | Class | weka.classifiers | Weka |
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ParallelMultipleClassifiersCombiner | Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple | Class | weka.classifiers | Weka |
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ParentSet | Helper class for Bayes Network classifiers. | Class | weka.classifiers.bayes.net | Weka |
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PART | Class for generating a PART decision list. | Class | weka.classifiers.rules | Weka |
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PlainText | Outputs the predictions in plain text. | Class | weka.classifiers.evaluation.output.prediction | Weka |
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PMMLClassifier | Abstract base class for all PMML classifiers. | Class | weka.classifiers.pmml.consumer | Weka |
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PolyKernel | The polynomial kernel : K(x, y) = ^p or K(x, y) = (+1)^p | Class | weka.classifiers.functions.supportVector | Weka |
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PrecomputedKernelMatrixKernel | This kernel is based on a static kernel matrix that is read from a file. | Class | weka.classifiers.functions.supportVector | Weka |
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PreConstructedLinearModel | This class encapsulates a linear regression function. | Class | weka.classifiers.trees.m5 | Weka |
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Prediction | Encapsulates a single evaluatable prediction: the predicted value plus the actual class value. | Interface | weka.classifiers.evaluation | Weka |
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PruneableClassifierTree | Class for handling a tree structure that can be pruned using a pruning set. | Class | weka.classifiers.trees.j48 | Weka |
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PruneableDecList | Class for handling a partial tree structure that can be pruned using aVersion:$Revision: 10153 $Author:Eibe Frank (eibe@cs. | Class | weka.classifiers.rules.part | Weka |
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Puk | The Pearson VII function-based universal kernel. | Class | weka.classifiers.functions.supportVector | Weka |
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RandomCommittee | Class for building an ensemble of randomizable base classifiers. | Class | weka.classifiers.meta | Weka |
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RandomForest | Class for constructing a forest of random trees. | Class | weka.classifiers.trees | Weka |
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RandomizableClassifier | Abstract utility class for handling settings common to randomizableVersion:$Revision: 10141 $Author:Eibe Frank (eibe@cs. | Class | weka.classifiers | Weka |
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RandomizableFilteredClassifier | Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. | Class | weka.classifiers.meta | Weka |
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RandomizableIteratedSingleClassifierEnhancer | Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner. | Class | weka.classifiers | Weka |
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RandomizableMultipleClassifiersCombiner | Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers based | Class | weka.classifiers | Weka |
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RandomizableParallelIteratedSingleClassifierEnhancer | Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single base | Class | weka.classifiers | Weka |
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RandomizableParallelMultipleClassifiersCombiner | Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple | Class | weka.classifiers | Weka |
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RandomizableSingleClassifierEnhancer | Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner. | Class | weka.classifiers | Weka |
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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. | Class | weka.classifiers.meta | Weka |
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RandomTree | Class for constructing a tree that considers K randomly chosen attributes at each node. | Class | weka.classifiers.trees | Weka |
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RBFKernel | The RBF kernel. | Class | weka.classifiers.functions.supportVector | Weka |
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RegOptimizer | Base class implementation for learning algorithm of SMOreg Valid options are: | Class | weka.classifiers.functions.supportVector | Weka |
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Regression | Class implementing import of PMML Regression model. | Class | weka.classifiers.pmml.consumer | Weka |
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RegressionAnalysis | Analyzes linear regression model by using the Student's t-test on each coefficient. | Class | weka.classifiers.evaluation | Weka |
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RegressionByDiscretization | A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized. | Class | weka.classifiers.meta | Weka |
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RegSMO | Implementation of SMO for support vector regression A. | Class | weka.classifiers.functions.supportVector | Weka |
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RegSMOImproved | Learn SVM for regression using SMO with Shevade, Keerthi, et al. | Class | weka.classifiers.functions.supportVector | Weka |
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RepeatedHillClimber | This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and | Class | weka.classifiers.bayes.net.search.global | Weka |
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RepeatedHillClimber | This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and | Class | weka.classifiers.bayes.net.search.local | Weka |
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REPTree | Fast decision tree learner. | Class | weka.classifiers.trees | Weka |
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ResidualModelSelection | Helper class for logistic model trees (weka. | Class | weka.classifiers.trees.lmt | Weka |
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ResidualSplit | Helper class for logistic model trees (weka. | Class | weka.classifiers.trees.lmt | Weka |
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Rule | Abstract class of generic ruleVersion:$Revision: 8034 $Author:Xin Xu (xx5@cs. | Class | weka.classifiers.rules | Weka |
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Rule | Generates a single m5 tree or ruleVersion:$Revision: 10169 $Author:Mark HallSee Also:Serialized Form | Class | weka.classifiers.trees.m5 | Weka |
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RuleNode | Constructs a node for use in an m5 tree or ruleVersion:$Revision: 10283 $Author:Mark Hall (mhall@cs. | Class | weka.classifiers.trees.m5 | Weka |
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RuleSetModel | Class implementing import of PMML RuleSetModel. | Class | weka.classifiers.pmml.consumer | Weka |
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RuleStats | This class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives, | Class | weka.classifiers.rules | Weka |
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Scoreable | Interface for allowing to score a classifierVersion:$Revision: 8034 $Author:Remco Bouckaert (rrb@xm. | Interface | weka.classifiers.bayes.net.search.local | Weka |
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SearchAlgorithm | This is the base class for all search algorithms for learning Bayes networks. | Class | weka.classifiers.bayes.net.search | Weka |
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SerializedClassifier | A wrapper around a serialized classifier model. | Class | weka.classifiers.misc | Weka |
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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). | Class | weka.classifiers.functions | Weka |
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SGDText | Implements stochastic gradient descent for learning a linear binary class SVM or binary class logistic regression on text data. | Class | weka.classifiers.functions | Weka |
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SGDText .Count | | Class | weka.classifiers.functions | Weka |
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SigmoidUnit | This can be used by the neuralnode to perform all it's computations (as a sigmoid unit). | Class | weka.classifiers.functions.neural | Weka |
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SimpleEstimator | SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has been | Class | weka.classifiers.bayes.net.estimate | Weka |
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SimpleLinearRegression | Learns a simple linear regression model. | Class | weka.classifiers.functions | Weka |
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SimpleLinearRegression | Stripped down version of SimpleLinearRegression. | Class | weka.classifiers.trees.lmt | Weka |
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SimpleLogistic | Classifier for building linear logistic regression models. | Class | weka.classifiers.functions | Weka |
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SimulatedAnnealing | This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring | Class | weka.classifiers.bayes.net.search.global | Weka |
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SimulatedAnnealing | This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring | Class | weka.classifiers.bayes.net.search.local | Weka |
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SingleClassifierEnhancer | Abstract utility class for handling settings common to meta classifiers that use a single base learner. | Class | weka.classifiers | Weka |
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SMO | Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier. | Class | weka.classifiers.functions | Weka |
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SMOreg | SMOreg implements the support vector machine for regression. | Class | weka.classifiers.functions | Weka |
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SMOset | Stores a set of integer of a given size. | Class | weka.classifiers.functions.supportVector | Weka |
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Sourcable | Interface for classifiers that can be converted to Java source. | Interface | weka.classifiers | Weka |
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Split | Base class for different split typesVersion:$Revision: 10531 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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SplitCandidate | Encapsulates a candidate splitVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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SplitCriterion | Abstract class for computing splitting criteria with respect to distributions of class values. | Class | weka.classifiers.trees.j48 | Weka |
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SplitEvaluate | Interface for objects that determine a split point on an attributeVersion:$Revision: 8034 $Author:Mark Hall (mhall@cs. | Interface | weka.classifiers.trees.m5 | Weka |
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SplitMetric | Base class for split metricsVersion:$Revision: 9720 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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SplitNode | Class for a node that splits the data in a Hoeffding treeVersion:$Revision: 10169 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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Stacking | Combines several classifiers using the stacking method. | Class | weka.classifiers.meta | Weka |
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StandardEvaluationMetric | Primarily a marker interface for a "standard" evaluation metric - i. | Interface | weka.classifiers.evaluation | Weka |
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Stats | Class implementing a statistical routine needed by J48 to compute its error estimate. | Class | weka.classifiers.trees.j48 | Weka |
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SupportVectorMachineModel | | Class | weka.classifiers.pmml.consumer | Weka |
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TabuSearch | This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure. | Class | weka.classifiers.bayes.net.search.global | Weka |
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TabuSearch | This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure. | Class | weka.classifiers.bayes.net.search.local | Weka |
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TAN | This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented | Class | weka.classifiers.bayes.net.search.global | Weka |
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TAN | This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented | Class | weka.classifiers.bayes.net.search.local | Weka |
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ThresholdCurve | Generates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes. | Class | weka.classifiers.evaluation | Weka |
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ThresholdProducingMetric | Some evaluation measures may optimize thresholds on the class probabilities. | Interface | weka.classifiers.evaluation | Weka |
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TreeModel | Class implementing import of PMML TreeModel. | Class | weka.classifiers.pmml.consumer | Weka |
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TwoClassStats | Encapsulates performance functions for two-class problems. | Class | weka.classifiers.evaluation | Weka |
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UnivariateNominalMultiwaySplit | A multiway split based on a single nominal attributeVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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UnivariateNumericBinarySplit | A binary split based on a single numeric attributeVersion:$Revision: 9705 $Author:Richard Kirkby (rkirkby@cs. | Class | weka.classifiers.trees.ht | Weka |
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UpdateableBatchProcessor | Updateable classifiers can implement this if they wish to be informed at the end of the training stream. | Interface | weka.classifiers | Weka |
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UpdateableClassifier | Interface to incremental classification models that can learn using one instance at a time. | Interface | weka.classifiers | Weka |
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Values | Stores some statistics. | Class | weka.classifiers.trees.m5 | Weka |
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VaryNode | Part of ADTree implementation. | Class | weka.classifiers.bayes.net | Weka |
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Vote | Class for combining classifiers. | Class | weka.classifiers.meta | Weka |
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VotedPerceptron | Implementation of the voted perceptron algorithm by Freund and Schapire. | Class | weka.classifiers.functions | Weka |
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WeightedInstancesHandlerWrapper | Generic wrapper around any classifier to enable weighted instances support. | Class | weka.classifiers.meta | Weka |
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WeightMass | Simple container for a weightVersion:$Revision: 9707 $Author:Mark Hall (mhall{[at]}pentaho{[dot]}com)See Also:Serialized Form | Class | weka.classifiers.trees.ht | Weka |
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XMLClassifier | This class serializes and deserializes a Classifier instance to andVersion:$Revision: 8034 $Author:FracPete (fracpete at waikato dot ac dot nz) | Class | weka.classifiers.xml | Weka |
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YongSplitInfo | Stores split information. | Class | weka.classifiers.trees.m5 | Weka |
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ZeroR | Class for building and using a 0-R classifier. | Class | weka.classifiers.rules | Weka |