| Modifier and Type | Class and Description |
|---|---|
class |
BayesNet
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. |
| Modifier and Type | Class and Description |
|---|---|
class |
BayesNetGenerator
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. |
class |
BIFReader
Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.
For more details on XML BIF see: Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998). |
class |
EditableBayesNet
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier. |
| Modifier and Type | Class and Description |
|---|---|
class |
AttributeSelectedClassifier
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
|
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.
|
| 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.
|
| Modifier and Type | Class and Description |
|---|---|
class |
TreeModel
Class implementing import of PMML TreeModel.
|
| Modifier and Type | Class and Description |
|---|---|
class |
HoeffdingTree
A Hoeffding tree (VFDT) is an incremental, anytime
decision tree induction algorithm that is capable of learning from massive
data streams, assuming that the distribution generating examples does not
change over time.
|
class |
J48
Class for generating a pruned or unpruned C4.5 decision tree.
|
class |
LMT
Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
|
class |
M5P
M5Base.
|
class |
RandomTree
Class for constructing a tree that considers K
randomly chosen attributes at each node.
|
class |
REPTree
Fast decision tree learner.
|
| Modifier and Type | Class and Description |
|---|---|
class |
C45PruneableClassifierTree
Class for handling a tree structure that can
be pruned using C4.5 procedures.
|
class |
ClassifierTree
Class for handling a tree structure used for
classification.
|
class |
NBTreeClassifierTree
Class for handling a naive bayes tree structure used for
classification.
|
class |
PruneableClassifierTree
Class for handling a tree structure that can
be pruned using a pruning set.
|
| Modifier and Type | Class and Description |
|---|---|
class |
Cobweb
Class implementing the Cobweb and Classit clustering algorithms.
Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers. |
class |
HierarchicalClusterer
Hierarchical clustering class.
|
Copyright © 2013 University of Waikato, Hamilton, NZ. All Rights Reserved.