| Package | Description |
|---|---|
| weka.classifiers.functions | |
| weka.classifiers.functions.supportVector | |
| weka.filters.unsupervised.attribute |
| Class and Description |
|---|
| Kernel
Abstract kernel.
|
| RegOptimizer
Base class implementation for learning algorithm of SMOreg
Valid options are:
|
| Class and Description |
|---|
| CachedKernel
Base class for RBFKernel and PolyKernel that implements a simple LRU.
|
| Kernel
Abstract kernel.
|
| PolyKernel
The polynomial kernel : K(x, y) = <x, y>^p or K(x, y) = (<x, y>+1)^p
Valid options are:
|
| RegOptimizer
Base class implementation for learning algorithm of SMOreg
Valid options are:
|
| RegSMO
Implementation of SMO for support vector regression as described in :
A.J. |
| Class and Description |
|---|
| Kernel
Abstract kernel.
|
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