/** * 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() { return new Parameters((LinearThresholdUnit.Parameters) super.getParameters()); }
/** * 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((LinearThresholdUnit.Parameters) super.getParameters()); return p; }
/** * 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((LinearThresholdUnit.Parameters) super.getParameters()); p.beta = beta; return p; }
/** * Creates a string representation of these parameters in which only those parameters that * differ from their default values are mentioned. **/ public String nonDefaultString() { String name = baseLTU.getClass().getName(); name = name.substring(name.lastIndexOf('.') + 1); return name + ": " + baseLTU.getParameters().nonDefaultString(); } }
/** * 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((LinearThresholdUnit.Parameters) super.getParameters()); p.confidence = confidence; p.initialVariance = initialVariance; p.variances = variances.emptyClone(); return p; }