/** Creates an example NominalToBinary */ public Filter getFilter() { NominalToBinary f = new NominalToBinary(); return f; }
/** * Main method for testing this class. * * @param argv should contain arguments to the filter: use -h for help */ public static void main(String[] argv) { runFilter(new NominalToBinary(), argv); } }
/** * Main method for testing this class. * * @param argv should contain arguments to the filter: use -h for help */ public static void main(String[] argv) { runFilter(new NominalToBinary(), argv); } }
/** Creates an example NominalToBinary */ public Filter getFilter() { NominalToBinary f = new NominalToBinary(); return f; }
m_numeric = false; m_random = null; m_nominalToBinaryFilter = new NominalToBinary(); m_sigmoidUnit = new SigmoidUnit(); m_linearUnit = new LinearUnit();
m_numeric = false; m_random = null; m_nominalToBinaryFilter = new NominalToBinary(); m_sigmoidUnit = new SigmoidUnit(); m_linearUnit = new LinearUnit();
nominalAttrRange.deleteCharAt(nominalAttrRange.lastIndexOf(rangeDelimiter)); try { nominalToBinaryFilter = new NominalToBinary(); nominalToBinaryFilter.setAttributeIndices(nominalAttrRange.toString()); nominalToBinaryFilter.setInputFormat(dataSet);
nomToBinFilter = new NominalToBinary(); try { nomToBinFilter = new NominalToBinary(); nomToBinFilter.setAttributeIndices(nominalAttrRange.toString()); nomToBinFilter.setInputFormat(dataSet);
m_ntob = new weka.filters.supervised.attribute.NominalToBinary(); } else { m_ntob = new weka.filters.unsupervised.attribute.NominalToBinary();
m_ntob = new weka.filters.supervised.attribute.NominalToBinary(); } else { m_ntob = new weka.filters.unsupervised.attribute.NominalToBinary();
m_Train = Filter.useFilter(m_Train, m_ReplaceMissingValues); m_NominalToBinary = new NominalToBinary(); m_NominalToBinary.setInputFormat(m_Train); m_Train = Filter.useFilter(m_Train, m_NominalToBinary);
m_Train = Filter.useFilter(m_Train, m_ReplaceMissingValues); m_NominalToBinary = new NominalToBinary(); m_NominalToBinary.setInputFormat(m_Train); m_Train = Filter.useFilter(m_Train, m_NominalToBinary);
nominalToBinaryFilter = new NominalToBinary(); nominalToBinaryFilter.setInputFormat(data); data = Filter.useFilter(data, nominalToBinaryFilter);
m_NominalToBinary = new NominalToBinary(); m_NominalToBinary.setInputFormat(data); data = Filter.useFilter(data, m_NominalToBinary);
m_NominalToBinary = new NominalToBinary(); m_NominalToBinary.setInputFormat(data); data = Filter.useFilter(data, m_NominalToBinary);
m_nominalToBinary = new weka.filters.supervised.attribute.NominalToBinary(); } else { m_nominalToBinary = new weka.filters.unsupervised.attribute.NominalToBinary();
m_nominalToBinary = new weka.filters.supervised.attribute.NominalToBinary(); } else { m_nominalToBinary = new weka.filters.unsupervised.attribute.NominalToBinary();
m_nominalToBinary = new NominalToBinary(); m_nominalToBinary.setInputFormat(data); data = Filter.useFilter(data, m_nominalToBinary);
m_NominalToBinary = new NominalToBinary(); m_NominalToBinary.setInputFormat(instances); instances = Filter.useFilter(instances, m_NominalToBinary);
Filter twoF = new NominalToBinary(); filters[0] = twoF; filters[1] = oneF;