/** * Returns an enumeration describing the available options * * @return an enumeration of all the available options */ @Override public Enumeration<Option> listOptions() { Vector<Option> result = new Vector<Option>(); result.addElement(new Option( "\tWhether to 0=normalize/1=standardize/2=neither.\n" + "\t(default 1=standardize)", "N", 1, "-N <num>")); result.addAll(Collections.list(super.listOptions())); return result.elements(); }
/** * Returns an enumeration describing the available options * * @return an enumeration of all the available options */ @Override public Enumeration<Option> listOptions() { Vector<Option> result = new Vector<Option>(); result.addElement(new Option("\tSet whether or not use empirical\n" + "\tlog-odds cut-off instead of 0", "C", 0, "-C")); result.addElement(new Option("\tSet the number of multiple runs \n" + "\tneeded for searching the MLE.", "R", 1, "-R <numOfRuns>")); result.addAll(Collections.list(super.listOptions())); return result.elements(); }
/** * Returns an enumeration describing the available options * * @return an enumeration of all the available options */ @Override public Enumeration<Option> listOptions() { Vector<Option> result = new Vector<Option>(); result.addElement(new Option("\tSet whether or not use empirical\n" + "\tlog-odds cut-off instead of 0", "C", 0, "-C")); result.addElement(new Option("\tSet the number of multiple runs \n" + "\tneeded for searching the MLE.", "R", 1, "-R <numOfRuns>")); result.addAll(Collections.list(super.listOptions())); return result.elements(); }
/** * Gets an enumeration describing the available options. * * @return an enumeration of all the available options. */ @Override public Enumeration<Option> listOptions() { Vector<Option> result = new Vector<Option>(); result.addElement(new Option( "\tThe PLS filter to use. Full classname of filter to include, " + "\tfollowed by scheme options.\n" + "\t(default: weka.filters.supervised.attribute.PLSFilter)", "filter", 1, "-filter <filter specification>")); result.addAll(Collections.list(super.listOptions())); if (getFilter() instanceof OptionHandler) { result.addElement(new Option("", "", 0, "\nOptions specific to filter " + getFilter().getClass().getName() + " ('-filter'):")); result.addAll(Collections.list(((OptionHandler) getFilter()) .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 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(); }
newVector.add(new Option("\tDon't replace missing values", "M", 0, "-M")); newVector.addAll(Collections.list(super.listOptions()));
newVector.add(new Option("\tDon't replace missing values", "M", 0, "-M")); newVector.addAll(Collections.list(super.listOptions()));
"-class-value-index <0-based index>")); newVector.addAll(Collections.list(super.listOptions()));
"stemmer", 1, "-stemmer <spec>")); newVector.addAll(Collections.list(super.listOptions()));
"-class-value-index <0-based index>")); newVector.addAll(Collections.list(super.listOptions()));
"stemmer", 1, "-stemmer <spec>")); newVector.addAll(Collections.list(super.listOptions()));
"An", 1, "-An [number of splits]")); result.addAll(Collections.list(super.listOptions()));
new Option("\tSeed for the random number generator when -B is used.\n\t(default = 1)", "seed", 1, "-seed <num>")); Enumeration en = super.listOptions(); while (en.hasMoreElements()) { Option op = (Option) en.nextElement();