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## weka.classifiers.functions.supportVector
Class PolyKernel

    java.lang.Object
      weka.classifiers.functions.supportVector.Kernel
          weka.classifiers.functions.supportVector.CachedKernel
              weka.classifiers.functions.supportVector.PolyKernel

All Implemented Interfaces:
  java.io.Serializable

Direct Known Subclasses:
  NormalizedPolyKernel

    public class PolyKernel

extends CachedKernel

The polynomial kernel : K(x, y) = ^p or K(x, y) = ( +1)^p

Version:
  $Revision: 1.1.2.2 $
Author:
  Eibe Frank (eibe@cs.waikato.ac.nz), Shane Legg (shane@intelligenesis.net) (sparse vector code), Stuart Inglis (stuart@reeltwo.com) (sparse vector code)
See Also:
  Serialized Form

Constructor Summary
`PolyKernel(Instances dataset, int cacheSize, double exponent, boolean lowerOrder)` Creates a new `PolyKernel` instance.

Method Summary

Methods inherited from class weka.classifiers.functions.supportVector.CachedKernel
`clean, eval, numCacheHits, numEvals`

Methods inherited from class java.lang.Object
`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### PolyKernel

    public PolyKernel(Instances dataset,
                      int cacheSize,
                      double exponent,
                      boolean lowerOrder)

  Creates a new `PolyKernel` instance.

  Parameters:
    `dataset` - the training dataset used.
    `cacheSize` - the size of the cache (a prime number)

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