/** * Instantiates this multiplexed learner using the specified base learning algorithm. * * @param n The name of the classifier. * @param base Instances of this learner will be multiplexed. * @param d This prediction will be returned during testing when the multiplexed * <code>Learner</code> does not exist. **/ public MuxLearner(String n, Learner base, String d) { super(n); Parameters p = new Parameters(); p.baseLearner = base; p.defaultPrediction = d; setParameters(p); network = new OVector(); }
/** * Retrieves the parameters that are set in this learner. * * @return An object containing all the values of the parameters that control the behavior of * this learning algorithm. **/ public Learner.Parameters getParameters() { Parameters p = new Parameters(super.getParameters()); p.baseLearner = baseLearner; p.defaultPrediction = defaultPrediction; return p; }