Examples of weka.classifiers.functions.GaussianProcesses

weka.classifiers.functions.GaussianProcesses

a.phy.cam.ac.uk/mackay/gpB.ps.gz} }

Valid options are:

 -D If set, classifier is run in debug mode and may output additional info to the console

 -L <double> Level of Gaussian Noise. (default: 1.0)

 -N Whether to 0=normalize/1=standardize/2=neither. (default: 0=normalize)

 -K <classname and parameters> The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)

  Options specific to kernel weka.classifiers.functions.supportVector.RBFKernel:

 -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)

 -G <num> The Gamma parameter. (default: 0.01)

@author Kurt Driessens (kurtd@cs.waikato.ac.nz) @version $Revision: 1.8 $

        byte[] data=ramout.toByteArray();
        ByteArrayInputStream   ramStrem=new ByteArrayInputStream(data);
        Instances wine = new Instances(new InputStreamReader(ramStrem));
        WekaForecaster forecaster = new WekaForecaster();
        forecaster.setFieldsToForecast(numberfield.toString());
        forecaster.setBaseForecaster(new GaussianProcesses());
        forecaster.getTSLagMaker().setTimeStampField("thedate"); // date time stamp
        forecaster.getTSLagMaker().setMinLag(1);
        forecaster.getTSLagMaker().setMaxLag(12); // monthly data
        forecaster.getTSLagMaker().setAddMonthOfYear(true);
        forecaster.getTSLagMaker().setAddQuarterOfYear(true);

Examples of weka.classifiers.functions.GaussianProcesses

Related Classes of weka.classifiers.functions.GaussianProcesses