List of usage examples for weka.core Option Option
public Option(String description, String name, int numArguments, String synopsis)
From source file:WLSVM.java
License:Open Source License
/** * Returns an enumeration describing the available options. * /*from w w w. ja v a 2 s. co m*/ * @return an enumeration of all the available options. */ public Enumeration listOptions() { Vector newVector = new Vector(13); newVector.addElement(new Option( "\t set type of SVM (default 0)\n" + "\t\t 0 = C-SVC\n" + "\t\t 1 = nu-SVC\n" + "\t\t 2 = one-class SVM\n" + "\t\t 3 = epsilon-SVR\n" + "\t\t 4 = nu-SVR", "S", 1, "-S <int>")); newVector.addElement(new Option("\t set type of kernel function (default 2)\n" + "\t\t 0 = linear: u'*v\n" + "\t\t 1 = polynomial: (gamma*u'*v + coef0)^degree\n" + "\t\t 2 = radial basis function: exp(-gamma*|u-v|^2)\n" + "\t\t 3 = sigmoid: tanh(gamma*u'*v + coef0)", "K", 1, "-K <int>")); newVector.addElement(new Option("\t set degree in kernel function (default 3)", "D", 1, "-D <int>")); newVector.addElement(new Option("\t set gamma in kernel function (default 1/k)", "G", 1, "-G <double>")); newVector.addElement(new Option("\t set coef0 in kernel function (default 0)", "R", 1, "-R <double>")); newVector.addElement(new Option("\t set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)", "C", 1, "-C <double>")); newVector .addElement(new Option("\t set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)", "N", 1, "-N <double>")); newVector.addElement(new Option("\t whether to normalize input data, 0 or 1 (default 0)", "Z", 1, "-Z")); newVector.addElement(new Option("\t set the epsilon in loss function of epsilon-SVR (default 0.1)", "P", 1, "-P <double>")); newVector.addElement(new Option("\t set cache memory size in MB (default 40)", "M", 1, "-M <double>")); newVector.addElement( new Option("\t set tolerance of termination criterion (default 0.001)", "E", 1, "-E <double>")); newVector.addElement( new Option("\t whether to use the shrinking heuristics, 0 or 1 (default 1)", "H", 1, "-H <int>")); newVector.addElement( new Option("\t whether to train a SVC or SVR model for probability estimates, 0 or 1 (default 0)", "B", 1, "-B <int>")); newVector.addElement(new Option("\t set the parameters C of class i to weight[i]*C, for C-SVC (default 1)", "W", 1, "-W <double>")); return newVector.elements(); }
From source file:Bilbo.java
License:Open Source License
/** * Returns an enumeration describing the available options. * * @return an enumeration of all the available options. *//*from w w w .ja v a 2s.c om*/ @Override public Enumeration<Option> listOptions() { Vector<Option> newVector = new Vector<Option>(3); newVector.addElement( new Option("\tSize of each bag, as a percentage of the\n" + "\ttraining set size. (default 100)", "P", 1, "-P")); newVector.addElement(new Option("\tCalculate the out of bag error.", "O", 0, "-O")); newVector.addElement(new Option("\tRepresent copies of instances using weights rather than explicitly.", "-represent-copies-using-weights", 0, "-represent-copies-using-weights")); newVector.addAll(Collections.list(super.listOptions())); return newVector.elements(); }
From source file:PrincipalComponents.java
License:Open Source License
/** * Returns an enumeration describing the available options. * <p>/*from w w w . ja v a2 s . c o m*/ * * @return an enumeration of all the available options. **/ @Override public Enumeration<Option> listOptions() { Vector<Option> newVector = new Vector<Option>(4); newVector.addElement(new Option("\tCenter (rather than standardize) the" + "\n\tdata and compute PCA using the covariance (rather" + "\n\t than the correlation) matrix.", "C", 0, "-C")); newVector.addElement( new Option("\tRetain enough PC attributes to account " + "\n\tfor this proportion of variance in " + "the original data.\n" + "\t(default = 0.95)", "R", 1, "-R")); newVector.addElement(new Option("\tTransform through the PC space and " + "\n\tback to the original space.", "O", 0, "-O")); newVector.addElement(new Option("\tMaximum number of attributes to include in " + "\n\ttransformed attribute names. (-1 = include all)", "A", 1, "-A")); return newVector.elements(); }
From source file:TextDirectoryLoader.java
License:Open Source License
/** * Lists the available options//w w w. jav a2 s .co m * * @return an enumeration of the available options */ public Enumeration listOptions() { Vector result = new Vector(); result.add(new Option("\tEnables debug output.\n" + "\t(default: off)", "D", 0, "-D")); result.add(new Option("\tStores the filename in an additional attribute.\n" + "\t(default: off)", "F", 0, "-F")); result.add(new Option("\tThe directory to work on.\n" + "\t(default: current directory)", "dir", 0, "-dir <directory>")); result.add(new Option( "\tThe character set to use, e.g UTF-8.\n\t" + "(default: use the default character set)", "charset", 1, "-charset <charset name>")); return result.elements(); }
From source file:ArrayLoader.java
License:Open Source License
/** * Returns an enumeration describing the available options. * * @return an enumeration of all the available options. */// www. j a v a 2s .c om public Enumeration listOptions() { Vector result = new Vector(); result.addElement(new Option( "\tThe range of attributes to force type to be NOMINAL.\n" + "\t'first' and 'last' are accepted as well.\n" + "\tExamples: \"first-last\", \"1,4,5-27,50-last\"\n" + "\t(default: -none-)", "N", 1, "-N <range>")); result.addElement(new Option( "\tThe range of attribute to force type to be STRING.\n" + "\t'first' and 'last' are accepted as well.\n" + "\tExamples: \"first-last\", \"1,4,5-27,50-last\"\n" + "\t(default: -none-)", "S", 1, "-S <range>")); result.addElement( new Option("\tThe string representing a missing value.\n" + "\t(default: ?)", "M", 1, "-M <str>")); return result.elements(); }
From source file:BaggingImprove.java
/** * Returns an enumeration describing the available options. * * @return an enumeration of all the available options. *///from w ww . j a v a 2s. c om @Override public Enumeration listOptions() { Vector newVector = new Vector(2); newVector.addElement( new Option("\tSize of each bag, as a percentage of the\n" + "\ttraining set size. (default 100)", "P", 1, "-P")); newVector.addElement(new Option("\tCalculate the out of bag error.", "O", 0, "-O")); Enumeration enu = super.listOptions(); while (enu.hasMoreElements()) { newVector.addElement(enu.nextElement()); } return newVector.elements(); }
From source file:REPTree.java
License:Open Source License
/** * Lists the command-line options for this classifier. * /*from w ww . j a v a2 s. c om*/ * @return an enumeration over all commandline options */ public Enumeration listOptions() { Vector newVector = new Vector(8); newVector.addElement(new Option("\tSet minimum number of instances per leaf " + "(default 2).", "M", 1, "-M <minimum number of instances>")); newVector.addElement(new Option( "\tSet minimum numeric class variance proportion\n" + "\tof train variance for split (default 1e-3).", "V", 1, "-V <minimum variance for split>")); newVector.addElement(new Option("\tNumber of folds for reduced error pruning " + "(default 3).", "N", 1, "-N <number of folds>")); newVector.addElement(new Option("\tSeed for random data shuffling (default 1).", "S", 1, "-S <seed>")); newVector.addElement(new Option("\tNo pruning.", "P", 0, "-P")); newVector.addElement(new Option("\tMaximum tree depth (default -1, no maximum)", "L", 1, "-L")); newVector.addElement(new Option("\tInitial class value count (default 0)", "I", 1, "-I")); newVector.addElement(new Option( "\tSpread initial count over all class values (i.e." + " don't use 1 per value)", "R", 0, "-R")); return newVector.elements(); }
From source file:NewRPISCE.java
License:Open Source License
/** * Returns an enumeration describing the available options. * * @return an enumeration of all the available options. *//*from ww w.j ava 2s . c o m*/ public Enumeration<Option> listOptions() { Vector<Option> newVector = new Vector<Option>(1); newVector.addElement(new Option("\tRandom number seed.\n" + "\t(default 1)", "S", 1, "-S <num>")); newVector.addAll(Collections.list(super.listOptions())); return newVector.elements(); }
From source file:REPRandomTree.java
License:Open Source License
/** * Lists the command-line options for this classifier. * /*from w w w . ja v a2s. c om*/ * @return an enumeration over all commandline options */ public Enumeration listOptions() { Vector newVector = new Vector(9); newVector.addElement(new Option("\tSet minimum number of instances per leaf " + "(default 2).", "M", 1, "-M <minimum number of instances>")); newVector.addElement(new Option( "\tSet minimum numeric class variance proportion\n" + "\tof train variance for split (default 1e-3).", "V", 1, "-V <minimum variance for split>")); newVector.addElement(new Option("\tNumber of folds for reduced error pruning " + "(default 3).", "N", 1, "-N <number of folds>")); newVector.addElement(new Option("\tSeed for random data shuffling (default 1).", "S", 1, "-S <seed>")); newVector.addElement(new Option("\tNo pruning.", "P", 0, "-P")); newVector.addElement(new Option("\tMaximum tree depth (default -1, no maximum)", "L", 1, "-L")); newVector.addElement(new Option("\tInitial class value count (default 0)", "I", 1, "-I")); newVector.addElement(new Option( "\tSpread initial count over all class values (i.e." + " don't use 1 per value)", "R", 0, "-R")); newVector.addElement(new Option("\tFraction of features to consider for splitting", "F", 1, "-F")); return newVector.elements(); }
From source file:MultiClassClassifier.java
License:Open Source License
/** * Returns an enumeration describing the available options * * @return an enumeration of all the available options */// ww w . ja va 2 s . c om public Enumeration listOptions() { Vector vec = new Vector(4); vec.addElement(new Option( "\tSets the method to use. Valid values are 0 (1-against-all),\n" + "\t1 (random codes), 2 (exhaustive code), and 3 (1-against-1). (default 0)\n", "M", 1, "-M <num>")); vec.addElement( new Option("\tSets the multiplier when using random codes. (default 2.0)", "R", 1, "-R <num>")); vec.addElement(new Option("\tUse pairwise coupling (only has an effect for 1-against1)", "P", 0, "-P")); Enumeration enu = super.listOptions(); while (enu.hasMoreElements()) { vec.addElement(enu.nextElement()); } return vec.elements(); }