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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