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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 polynomeal 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/dissalow 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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