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See:
Description
| Interface Summary | |
|---|---|
| SuffixTreeKernel.DepthScaler | Encapsulates the scale factor to apply at a given depth. |
| Class Summary | |
|---|---|
| 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 | |
Tools for use of the SVM package.
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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