/** * Main method for testing this class. * * @param argv should contain the following arguments: -t training file */ public static void main(String[] argv) { runEvaluator(new SymmetricalUncertAttributeEval(), argv); } }
/** * Gets the current settings of WrapperSubsetEval. * * @return an array of strings suitable for passing to setOptions() */ @Override public String[] getOptions() { String[] options = new String[1]; int current = 0; if (!getMissingMerge()) { options[current++] = "-M"; } while (current < options.length) { options[current++] = ""; } return options; }
/** * Constructor */ public SymmetricalUncertAttributeEval() { resetOptions(); }
/** Creates a default SymmetricalUncertAttributeEval */ public ASEvaluation getEvaluator() { return new SymmetricalUncertAttributeEval(); }
/** * Parses a given list of options. * <p/> * * <!-- options-start --> Valid options are: * <p/> * * <pre> * -M * treat missing values as a seperate value. * </pre> * * <!-- options-end --> * * @param options the list of options as an array of strings * @throws Exception if an option is not supported **/ @Override public void setOptions(String[] options) throws Exception { resetOptions(); setMissingMerge(!(Utils.getFlag('M', options))); }
/** * Initializes a symmetrical uncertainty attribute evaluator. Discretizes all * attributes that are numeric. * * @param data set of instances serving as training data * @throws Exception if the evaluator has not been generated successfully */ @Override public void buildEvaluator(Instances data) throws Exception { // can evaluator handle data? getCapabilities().testWithFail(data); m_trainInstances = data; m_classIndex = m_trainInstances.classIndex(); m_numInstances = m_trainInstances.numInstances(); Discretize disTransform = new Discretize(); disTransform.setUseBetterEncoding(true); disTransform.setInputFormat(m_trainInstances); m_trainInstances = Filter.useFilter(m_trainInstances, disTransform); m_numClasses = m_trainInstances.attribute(m_classIndex).numValues(); }
/** Creates a default SymmetricalUncertAttributeEval */ public ASEvaluation getEvaluator() { return new SymmetricalUncertAttributeEval(); }
/** * Parses a given list of options. * <p/> * * <!-- options-start --> Valid options are: * <p/> * * <pre> * -M * treat missing values as a seperate value. * </pre> * * <!-- options-end --> * * @param options the list of options as an array of strings * @throws Exception if an option is not supported **/ @Override public void setOptions(String[] options) throws Exception { resetOptions(); setMissingMerge(!(Utils.getFlag('M', options))); }
/** * Initializes a symmetrical uncertainty attribute evaluator. Discretizes all * attributes that are numeric. * * @param data set of instances serving as training data * @throws Exception if the evaluator has not been generated successfully */ @Override public void buildEvaluator(Instances data) throws Exception { // can evaluator handle data? getCapabilities().testWithFail(data); m_trainInstances = data; m_classIndex = m_trainInstances.classIndex(); m_numInstances = m_trainInstances.numInstances(); Discretize disTransform = new Discretize(); disTransform.setUseBetterEncoding(true); disTransform.setInputFormat(m_trainInstances); m_trainInstances = Filter.useFilter(m_trainInstances, disTransform); m_numClasses = m_trainInstances.attribute(m_classIndex).numValues(); }
/** * Main method for testing this class. * * @param argv should contain the following arguments: -t training file */ public static void main(String[] argv) { runEvaluator(new SymmetricalUncertAttributeEval(), argv); } }
/** * Constructor */ public SymmetricalUncertAttributeEval() { resetOptions(); }
/** * Gets the current settings of WrapperSubsetEval. * * @return an array of strings suitable for passing to setOptions() */ @Override public String[] getOptions() { String[] options = new String[1]; int current = 0; if (!getMissingMerge()) { options[current++] = "-M"; } while (current < options.length) { options[current++] = ""; } return options; }