| AbstractLoader |
Abstract class gives default implementation of setSource
methods.
|
| Attribute |
Class for handling an attribute.
|
| AttributeStats |
A Utility class that contains summary information on an
the values that appear in a dataset for a particular attribute.
|
| BinC45ModelSelection |
Class for selecting a C4.5-like binary (!) split for a given dataset.
|
| BinC45Split |
Class implementing a binary C4.5-like split on an attribute.
|
| C45ModelSelection |
Class for selecting a C4.5-type split for a given dataset.
|
| C45PruneableClassifierTree |
Class for handling a tree structure that can
be pruned using C4.5 procedures.
|
| C45Split |
Class implementing a C4.5-type split on an attribute.
|
| Classifier |
Abstract classifier.
|
| ClassifierSplitModel |
Abstract class for classification models that can be used
recursively to split the data.
|
| ClassifierTree |
Class for handling a tree structure used for classification.
|
| ConverterUtils |
Utility routines for the converter package.
|
| CostMatrix |
Class for storing and manipulating a misclassification cost matrix.
|
| CSVLoader |
Reads a text file that is comma or tab delimited..
|
| Discrimination |
|
| Distribution |
Class for handling a distribution of class values.
|
| EntropyBasedSplitCrit |
"Abstract" class for computing splitting criteria
based on the entropy of a class distribution.
|
| Evaluation |
Class for evaluating machine learning models.
|
| FastVector |
Implements a fast vector class without synchronized
methods.
|
| Filter |
An abstract class for instance filters: objects that take instances
as input, carry out some transformation on the instance and then
output the instance.
|
| GainRatioSplitCrit |
Class for computing the gain ratio for a given distribution.
|
| InfoGainSplitCrit |
Class for computing the information gain for a given distribution.
|
| Instance |
Class for handling an instance.
|
| Instances |
Class for handling an ordered set of weighted instances.
|
| J48 |
Class for generating an unpruned or a pruned C4.5 decision tree.
|
| J48WithNDCs |
Class for generating an unpruned or a pruned C4.5 decision tree.
|
| KernelEstimator |
Simple kernel density estimator.
|
| Massaging |
Class for building and using a Classyfing without Discriminating classifier.
|
| Matrix |
Deprecated.
|
| ModelSelection |
Abstract class for model selection criteria.
|
| NaiveBayesSimple |
Class for building and using a simple Naive Bayes classifier.
|
| NoSplit |
Class implementing a "no-split"-split.
|
| Option |
Class to store information about an option.
|
| PrefrentialSamplingFilter |
|
| ProtectedProperties |
Simple class that extends the Properties class so that the properties are
unable to be modified.
|
| PruneableClassifierTree |
Class for handling a tree structure that can
be pruned using a pruning set.
|
| Queue |
Class representing a FIFO queue.
|
| Range |
Class representing a range of cardinal numbers.
|
| RemoveSAFilter |
An instance filter that deletes a range of attributes from the dataset.
|
| SelectedTag |
Represents a selected value from a finite set of values, where each
value is a Tag (i.e.
|
| SerializedObject |
Class for storing an object in serialized form in memory.
|
| SparseInstance |
Class for storing an instance as a sparse vector.
|
| SplitCriterion |
Abstract class for computing splitting criteria
with respect to distributions of class values.
|
| Statistics |
Class implementing some distributions, tests, etc.
|
| Stats |
Class implementing a statistical routine needed by J48 to
compute its error estimate.
|
| Tag |
A Tag simply associates a numeric ID with a String description.
|
| Utils |
Class implementing some simple utility methods.
|