/** * Returns an enumeration describing the available options. * * @return an enumeration of all the available options. */ @Override public Enumeration<Option> listOptions() { java.util.Vector<Option> result = new java.util.Vector<Option>(); result.addElement(new Option( "\tLevel of Gaussian Noise wrt transformed target." + " (default 1)", "L", 1, "-L <double>")); result.addElement(new Option( "\tWhether to 0=normalize/1=standardize/2=neither. " + "(default 0=normalize)", "N", 1, "-N")); result.addElement(new Option("\tThe Kernel to use.\n" + "\t(default: weka.classifiers.functions.supportVector.PolyKernel)", "K", 1, "-K <classname and parameters>")); result.addAll(Collections.list(super.listOptions())); result.addElement(new Option("", "", 0, "\nOptions specific to kernel " + getKernel().getClass().getName() + ":")); result .addAll(Collections.list(((OptionHandler) getKernel()).listOptions())); return result.elements(); }
/** * Returns an enumeration describing the available options. * * @return an enumeration of all the available options. */ @Override public Enumeration<Option> listOptions() { java.util.Vector<Option> result = new java.util.Vector<Option>(); result.addElement(new Option( "\tLevel of Gaussian Noise wrt transformed target." + " (default 1)", "L", 1, "-L <double>")); result.addElement(new Option( "\tWhether to 0=normalize/1=standardize/2=neither. " + "(default 0=normalize)", "N", 1, "-N")); result.addElement(new Option("\tThe Kernel to use.\n" + "\t(default: weka.classifiers.functions.supportVector.PolyKernel)", "K", 1, "-K <classname and parameters>")); result.addAll(Collections.list(super.listOptions())); result.addElement(new Option("", "", 0, "\nOptions specific to kernel " + getKernel().getClass().getName() + ":")); result .addAll(Collections.list(((OptionHandler) getKernel()).listOptions())); return result.elements(); }
/** * Returns default capabilities of the classifier. * * @return the capabilities of this classifier */ @Override public Capabilities getCapabilities() { Capabilities result = getKernel().getCapabilities(); result.setOwner(this); // attribute result.enableAllAttributeDependencies(); // with NominalToBinary we can also handle nominal attributes, but only // if the kernel can handle numeric attributes if (result.handles(Capability.NUMERIC_ATTRIBUTES)) { result.enable(Capability.NOMINAL_ATTRIBUTES); } result.enable(Capability.MISSING_VALUES); // class result.disableAllClasses(); result.disableAllClassDependencies(); result.disable(Capability.NO_CLASS); result.enable(Capability.NUMERIC_CLASS); result.enable(Capability.DATE_CLASS); result.enable(Capability.MISSING_CLASS_VALUES); return result; }
/** * Returns default capabilities of the classifier. * * @return the capabilities of this classifier */ @Override public Capabilities getCapabilities() { Capabilities result = getKernel().getCapabilities(); result.setOwner(this); // attribute result.enableAllAttributeDependencies(); // with NominalToBinary we can also handle nominal attributes, but only // if the kernel can handle numeric attributes if (result.handles(Capability.NUMERIC_ATTRIBUTES)) { result.enable(Capability.NOMINAL_ATTRIBUTES); } result.enable(Capability.MISSING_VALUES); // class result.disableAllClasses(); result.disableAllClassDependencies(); result.disable(Capability.NO_CLASS); result.enable(Capability.NUMERIC_CLASS); result.enable(Capability.DATE_CLASS); result.enable(Capability.MISSING_CLASS_VALUES); return result; }