| Interface | Description |
|---|---|
| IntervalEstimator |
Interface for classifiers that can output confidence intervals
|
| IterativeClassifier |
Interface for classifiers that can induce models of growing
complexity one step at a time.
|
| Sourcable |
Interface for classifiers that can be converted to Java source.
|
| UpdateableClassifier |
Interface to incremental classification models that can learn using
one instance at a time.
|
| Class | Description |
|---|---|
| BVDecompose |
Class for performing a Bias-Variance decomposition on any classifier using the method specified in:
Ron Kohavi, David H. |
| BVDecomposeSegCVSub |
This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1).
The Kohavi and Wolpert definition of bias and variance is specified in (2). The Webb definition of bias and variance is specified in (3). Geoffrey I. |
| CheckClassifier |
Class for examining the capabilities and finding problems with
classifiers.
|
| CheckSource |
A simple class for checking the source generated from Classifiers
implementing the
weka.classifiers.Sourcable interface. |
| Classifier |
Abstract classifier.
|
| CostMatrix |
Class for storing and manipulating a misclassification cost matrix.
|
| Evaluation |
Class for evaluating machine learning models.
|
| IteratedSingleClassifierEnhancer |
Abstract utility class for handling settings common to
meta classifiers that build an ensemble from a single base learner.
|
| MultipleClassifiersCombiner |
Abstract utility class for handling settings common to
meta classifiers that build an ensemble from multiple classifiers.
|
| RandomizableClassifier |
Abstract utility class for handling settings common to randomizable
classifiers.
|
| RandomizableIteratedSingleClassifierEnhancer |
Abstract utility class for handling settings common to randomizable
meta classifiers that build an ensemble from a single base learner.
|
| RandomizableMultipleClassifiersCombiner |
Abstract utility class for handling settings common to randomizable
meta classifiers that build an ensemble from multiple classifiers based
on a given random number seed.
|
| RandomizableSingleClassifierEnhancer |
Abstract utility class for handling settings common to randomizable
meta classifiers that build an ensemble from a single base learner.
|
| SingleClassifierEnhancer |
Abstract utility class for handling settings common to meta
classifiers that use a single base learner.
|