Interface | Description |
---|---|
DistanceFunction |
Represents a distance function between two
testing examples.
|
FeatureEntry |
Interface representing a feature
within an example.
|
LibSVMDataSet.ResultInterpreter |
Method by which to interpret the example result
as an object
|
TestingExample |
Represents a fixed-size sequence of
features without an associated result.
|
Class | Description |
---|---|
ClassificationGUI |
Demo GUI that provides a list of datasets and classifiers
as well as a run button.
|
Classifier |
Represents a classifier
|
DataSet |
Represents a set of examples
|
DenseExample |
An array-backed example, useful in situations
in which most if not all features are non-zero.
|
EuclideanDistanceSquared |
Implements the squared euclidean distance
between examples.
|
Example |
Represents a fixed-size sequence of
features with an associated result.
|
HiddenPatternDataSet |
A dataset based upon a set of patterns, each
a result object and a set of feature number/value pairs.
|
LibSVMDataSet |
A dataset from an input stream formatted ala LibSVM
|
ListDataSet |
ArrayList-backed DataSet implementation
|
MNISTGUI |
Visualizes a subset of MNIST using a 1-NN classifier
|
NearestNeighborClassifier |
Implements the 1-NN algorithm (classifies by
finding the closest training example).
|
SparseExample |
Implements an example by storing index/value pairs,
useful in situations where many/most of the example
features are 0
|
TieBreaker<T> |
A general mechanism by which to fairly choose
the "winner" in a stream of objects of unknown size
(Related: http://en.wikipedia.org/wiki/Reservoir_sampling).
|
ZeroRClassifier |
Implements the ZeroR classifier (uses the most
frequent result from the training set as the
result for any testing example)
|
Exception | Description |
---|---|
HiddenPatternDataSet.PatternException |
Exception class for errors adding patterns
|