| Package | Description | 
|---|---|
| weka.classifiers | |
| weka.classifiers.lazy | |
| weka.classifiers.meta | |
| weka.classifiers.misc | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
IteratedSingleClassifierEnhancer
Abstract utility class for handling settings common to
 meta classifiers that build an ensemble from a single base learner. 
 | 
class  | 
ParallelIteratedSingleClassifierEnhancer
Abstract utility class for handling settings common to
 meta classifiers that build an ensemble in parallel from a single
 base learner. 
 | 
class  | 
RandomizableIteratedSingleClassifierEnhancer
Abstract utility class for handling settings common to randomizable
 meta classifiers that build an ensemble from a single base learner. 
 | 
class  | 
RandomizableParallelIteratedSingleClassifierEnhancer
Abstract utility class for handling settings common to randomizable
 meta classifiers that build an ensemble in parallel from a single base
 learner. 
 | 
class  | 
RandomizableSingleClassifierEnhancer
Abstract utility class for handling settings common to randomizable
 meta classifiers that build an ensemble from a single base learner. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
LWL
Locally weighted learning. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
AdaBoostM1
Class for boosting a nominal class classifier using the Adaboost M1 method. 
 | 
class  | 
AdditiveRegression
Meta classifier that enhances the performance of a regression base classifier. 
 | 
class  | 
AttributeSelectedClassifier
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier. 
 | 
class  | 
Bagging
Class for bagging a classifier to reduce variance. 
 | 
class  | 
ClassificationViaRegression
Class for doing classification using regression methods. 
 | 
class  | 
CostSensitiveClassifier
A metaclassifier that makes its base classifier cost-sensitive. 
 | 
class  | 
CVParameterSelection
Class for performing parameter selection by cross-validation for any classifier. 
For more information, see: R.  | 
class  | 
FilteredClassifier
Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. 
 | 
class  | 
LogitBoost
Class for performing additive logistic regression. 
 | 
class  | 
MultiClassClassifier
A metaclassifier for handling multi-class datasets with 2-class classifiers. 
 | 
class  | 
MultiClassClassifierUpdateable
A metaclassifier for handling multi-class datasets with 2-class classifiers. 
 | 
class  | 
RandomCommittee
Class for building an ensemble of randomizable base classifiers. 
 | 
class  | 
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  | 
RegressionByDiscretization
A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
InputMappedClassifier
Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure. 
 | 
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