How to use weka.classifiers

 Classifier cModel = (Classifier)new NaiveBayes();  
cModel.buildClassifier(isTrainingSet);  

weka.core.SerializationHelper.write("/some/where/nBayes.model", cModel);

Classifier cls = (Classifier) weka.core.SerializationHelper.read("/some/where/nBayes.model");

// Test the model
Evaluation eTest = new Evaluation(isTrainingSet);
eTest.evaluateModel(cls, isTrainingSet);

 //load model
String rootPath="/some/where/"; 
Classifier cls = (Classifier) weka.core.SerializationHelper.read(rootPath+"tree.model");

//predict instance class values
Instances originalTrain= //load or create Instances to predict

//which instance to predict class value
int s1=0;  

//perform your prediction
double value=cls.classifyInstance(originalTrain.instance(s1));

//get the name of the class value
String prediction=originalTrain.classAttribute().value((int)value); 

System.out.println("The predicted value of instance "+
          Integer.toString(s1)+
          ": "+prediction);

public Evaluation classify(Classifier model, Instances trainingSet, Instances testingSet) throws Exception {
  Evaluation evaluation = new Evaluation(trainingSet);
  model.buildClassifier(trainingSet);
  evaluation.evaluateModel(model, testingSet);
  return evaluation;
}

/**
 * Calculates the class membership probabilities for the given test
 * instance.
 *
 * @param instance     the instance to be classified
 * @return         preedicted class probability distribution
 * @throws Exception     if distribution can't be computed successfully
 */
public double[] distributionForInstance(Instance instance) throws Exception {
 return m_Classifier.distributionForInstance(instance);
}

/**
 * configures the CheckClassifier instance used throughout the tests
 * 
 * @return    the fully configured CheckClassifier instance used for testing
 */
protected CheckClassifier getTester() {
 CheckClassifier     result;
 
 result = super.getTester();
 result.setNumInstances(40);
 
 return result;
}

private boolean replaceStrings(Instances dataset) throws Exception {
 boolean nonDouble = false;
 for (int i = 0; i < m_size; i++) {
  for (int j = 0; j < m_size; j++) {
   if (getCell(i, j) instanceof String) {
    setCell(i, j, new InstanceExpression((String) getCell(i, j), dataset));
    nonDouble = true;
   } else if (getCell(i, j) instanceof InstanceExpression) {
    nonDouble = true;
   }
  }
 }
 return nonDouble;
}

/**
 * tests whether the scheme declares a serialVersionUID.
 */
public void testSerialVersionUID() {
 boolean[] result;
 result = m_Tester.declaresSerialVersionUID();
 if (!result[0]) {
  fail("Doesn't declare serialVersionUID!");
 }
}

/**
 * tests whether the toString method of the classifier works even though the
 * classifier hasn't been built yet.
 */
public void testToString() {
 boolean[] result;
 result = m_Tester.testToString();
 if (!result[0]) {
  fail("Error in toString() method!");
 }
}

/**
 * returns a custom PostProcessor for the CheckClassifier datasets..
 * 
 * @return        a custom PostProcessor
 * @see AbsPostProcessor
 */
protected PostProcessor getPostProcessor() {
 return new AbsPostProcessor();
}

/**
 * Same as size
 * 
 * @return the number of rows
 */
public int numRows() {
 return size();
}

/**
 * returns a string for the class type
 * 
 * @param type the class type
 * @return the class type as string
 */
protected String getClassTypeString(int type) {
 return CheckClassifier.attributeTypeToString(type);
}

/**
 * Returns the distribution for the given instance.
 *
 * @param instance     the test instance
 * @return         the distribution array
 * @throws Exception     if distribution can't be computed successfully
 */
@Override
public double[] distributionForInstance(Instance instance) throws Exception {
  return m_Classifier.distributionForInstance(instance);
}

/**
 * configures the CheckClassifier instance used throughout the tests
 * 
 * @return    the fully configured CheckClassifier instance used for testing
 */
protected CheckClassifier getTester() {
 CheckClassifier     result;
 
 result = super.getTester();
 result.setNumInstances(40);
 
 return result;
}

/**
 * tests whether the scheme declares a serialVersionUID.
 */
public void testSerialVersionUID() {
 boolean[] result;
 result = m_Tester.declaresSerialVersionUID();
 if (!result[0]) {
  fail("Doesn't declare serialVersionUID!");
 }
}

/**
 * tests whether the toString method of the classifier works even though the
 * classifier hasn't been built yet.
 */
public void testToString() {
 boolean[] result;
 result = m_Tester.testToString();
 if (!result[0]) {
  fail("Error in toString() method!");
 }
}

/**
 * returns a custom PostProcessor for the CheckClassifier datasets..
 * 
 * @return        a custom PostProcessor
 * @see AbsPostProcessor
 */
protected PostProcessor getPostProcessor() {
 return new AbsPostProcessor();
}

/**
 * Returns the distribution for the given instance.
 *
 * @param instance     the test instance
 * @return         the distribution array
 * @throws Exception     if distribution can't be computed successfully
 */
@Override
public double[] distributionForInstance(Instance instance) throws Exception {
  return m_Classifier.distributionForInstance(instance);
}

/**
 * configures the CheckClassifier instance used throughout the tests
 * 
 * @return    the fully configured CheckClassifier instance used for testing
 */
protected CheckClassifier getTester() {
 CheckClassifier     result;
 
 result = super.getTester();
 result.setNumInstances(60);
 
 return result;
}

/**
 * returns a custom PostProcessor for the CheckClassifier datasets..
 * 
 * @return        a custom PostProcessor
 * @see AbsPostProcessor
 */
protected PostProcessor getPostProcessor() {
 return new AbsPostProcessor();
}

/**
 * configures the CheckClassifier instance used throughout the tests
 * 
 * @return    the fully configured CheckClassifier instance used for testing
 */
protected CheckClassifier getTester() {
 CheckClassifier     result;
 
 result = super.getTester();
 result.setNumInstances(40);
 
 return result;
}