@Test public void testSetLearningRate() { double learningRate = 1; learner.setLearningRate(learningRate); Assert.assertEquals(learningRate, learner.getLearningRate()); }
public void setLearningRate(double learningRate) { if (learningRate <= 0 || learningRate > 1) { throw new IllegalArgumentException("The learning rate must be greater than 0 and no more than 1. " + "Entered value is : " + learningRate); } this.learningRate = learningRate; }
BPMLL extends MultiLabelLearnerBase { public void setLearningRate(double learningRate) { if (learningRate <= 0 || learningRate > 1) { throw new IllegalArgumentException("The learning rate must be greater than 0 and no more than 1. " + "Entered value is : " + learningRate); } this.learningRate = learningRate; } }
BPMLL extends MultiLabelLearnerBase { public void setLearningRate(double learningRate) { if (learningRate <= 0 || learningRate > 1) { throw new IllegalArgumentException("The learning rate must be greater than 0 and no more than 1. " + "Entered value is : " + learningRate); } this.learningRate = learningRate; } BPMLL();  BPMLL(long randomnessSeed); }
BPMLL extends MultiLabelLearnerBase { public void setLearningRate(double learningRate) { if (learningRate <= 0 || learningRate > 1) { throw new IllegalArgumentException("The learning rate must be greater than 0 and no more than 1. " + "Entered value is : " + learningRate); } this.learningRate = learningRate; } BPMLL();  BPMLL(long randomnessSeed); void setHiddenLayers(int[] hiddenLayers); int[] getHiddenLayers(); void setLearningRate(double learningRate); double getLearningRate(); void setWeightsDecayRegularization(double weightsDecayCost); double getWeightsDecayRegularization(); void setTrainingEpochs(int epochs); int getTrainingEpochs(); void setNormalizeAttributes(boolean normalize); boolean getNormalizeAttributes(); String globalInfo(); @Override TechnicalInformation getTechnicalInformation(); MultiLabelOutput makePredictionInternal(Instance instance); }
BPMLL extends MultiLabelLearnerBase { public void setLearningRate(double learningRate) { if (learningRate <= 0 || learningRate > 1) { throw new IllegalArgumentException("The learning rate must be greater than 0 and no more than 1. " + "Entered value is : " + learningRate); } this.learningRate = learningRate; } BPMLL();  BPMLL(long randomnessSeed); void setHiddenLayers(int[] hiddenLayers); int[] getHiddenLayers(); void setLearningRate(double learningRate); double getLearningRate(); void setWeightsDecayRegularization(double weightsDecayCost); double getWeightsDecayRegularization(); void setTrainingEpochs(int epochs); int getTrainingEpochs(); void setNormalizeAttributes(boolean normalize); boolean getNormalizeAttributes(); String globalInfo(); @Override TechnicalInformation getTechnicalInformation(); MultiLabelOutput makePredictionInternal(Instance instance);  }