/** * 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.weakLearner = weakLearner; p.rounds = rounds; 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(super.getParameters()); p.smoothing = smoothing; 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(super.getParameters()); p.baseLTU = baseLTU; 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(super.getParameters()); p.baseClassifier = baseClassifier; p.attributeString = attributeString; 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(super.getParameters()); p.weightVector = weightVector; p.learningRate = learningRate; 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(super.getParameters()); p.baseLearner = baseLearner; p.defaultPrediction = defaultPrediction; 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(super.getParameters()); p.C = C; p.epsilon = epsilon; p.bias = bias; p.solverType = solverType; p.displayLL = displayLL; p.featurePruningThreshold = this.featurePruningThreshold; 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 result = super.nonDefaultString(); String name = baseLearner.getClass().getName(); name = name.substring(name.lastIndexOf('.') + 1); if (!defaultPrediction.equals(MuxLearner.defaultDefaultPrediction)) result += "defaultPrediction = " + defaultPrediction + ", "; result += name + ": " + baseLearner.getParameters().nonDefaultString(); return result; } }
/** * 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.learningRate = learningRate; p.weightVector = weightVector.emptyClone(); p.initialWeight = initialWeight; p.threshold = threshold; p.positiveThickness = positiveThickness; p.negativeThickness = negativeThickness; p.featurePruningThreshold = featurePruningThreshold; return p; }