Examples of weka.classifiers.functions.supportVector.PolyKernel

Package weka.classifiers.functions.supportVector

Examples of weka.classifiers.functions.supportVector.PolyKernel

weka.classifiers.functions.supportVector.PolyKernel

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

Valid options are:

 -D Enables debugging output (if available) to be printed. (default: off)

 -no-checks Turns off all checks - use with caution! (default: checks on)

 -C <num> The size of the cache (a prime number), 0 for full cache and  -1 to turn it off. (default: 250007)

 -E <num> The Exponent to use. (default: 1.0)

 -L Use lower-order terms. (default: no)

@author Eibe Frank (eibe@cs.waikato.ac.nz) @author Shane Legg (shane@intelligenesis.net) (sparse vector code) @author Stuart Inglis (stuart@reeltwo.com) (sparse vector code) @version $Revision: 5808 $

      tmpStr        = tmpOptions[0];
      tmpOptions[0] = "";
      setKernel(Kernel.forName(tmpStr, tmpOptions));
    }
    else {
      setKernel(new PolyKernel());
    }
  }

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      tmpStr        = tmpOptions[0];
      tmpOptions[0] = "";
      setKernel(Kernel.forName(tmpStr, tmpOptions));
    }
    else {
      setKernel(new PolyKernel());
    }
  }

View Full Code Here

      tmpStr        = tmpOptions[0];
      tmpOptions[0] = "";
      setKernel(Kernel.forName(tmpStr, tmpOptions));
    }
    else {
      setKernel(new PolyKernel());
    }
  }

View Full Code Here

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weka.classifiers.functions.SMOreg

weka.classifiers.functions.SVMreg

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weka.core.Option

java.util.Enumeration

java.util.Vector

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