instances = new Instances(instances); instances.deleteWithMissingClass();
    public void buildClassifier(Instances instances) throws Exception {        // Check that class is nominal        if (!instances.classAttribute().isNominal()) {            throw new UnsupportedClassTypeException("BayesNet: nominal class, please.");        }		// ensure we have a data set with discrete variables only and with no missing values		instances = normalizeDataSet(instances);        // Copy the instances        m_Instances = new Instances(instances);        // sanity check: need more than 1 variable in datat set        m_NumClasses = instances.numClasses();        // initialize ADTree        if (m_bUseADTree) {            m_ADTree = ADNode.makeADTree(instances);            //      System.out.println("Oef, done!");        }        // build the network structure        initStructure();        // build the network structure        buildStructure();        // build the set of CPTs        estimateCPTs();        // Save space        // m_Instances = new Instances(m_Instances, 0);        m_ADTree = null;    } // buildClassifier