| Interface | Description |
|---|---|
| SuffixTreeKernel.DepthScaler |
Encapsulates the scale factor to apply at a given depth.
|
| Class | Description |
|---|---|
| ClassifierExample |
A simple toy example that allows you to put points on a canvas, and find a
polynomial hyperplane to seperate them.
|
| ClassifierExample.PointClassifier |
An extention of JComponent that contains the points & encapsulates the
classifier.
|
| Classify | |
| SuffixTreeKernel |
Computes the dot-product of two suffix-trees as the sum of the products
of the counts of all nodes they have in common.
|
| SuffixTreeKernel.MultipleScalar |
Scale using a multiple of two DepthScalers.
|
| SuffixTreeKernel.NullModelScaler |
Scales by 4^depth - equivalent to dividing by a probablistic flatt prior
null model
|
| SuffixTreeKernel.SelectionScalar |
Scale using a BitSet to allow/disallow depths.
|
| SuffixTreeKernel.UniformScaler |
Scale all depths by 1.0
|
| SVM_Light | |
| SVM_Light.LabelledVector | |
| Train | |
| TrainRegression |
This provides practical programs for using SVMs to classify or regress real data. It also contains graphical demonstrations to explain how SVM works.
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