@Test public void test() throws Exception { SVBFadingExample.main(null); }
public static void main(String[] args) throws Exception { DataStream<DataInstance> data = DataStreamLoader.open("datasets/simulated/WasteIncineratorSample.arff"); SVBFading parameterLearningAlgorithm = new SVBFading(); parameterLearningAlgorithm.setDAG(DAGGenerator.getHiddenNaiveBayesStructure(data.getAttributes(),"GlobalHidden", 2)); parameterLearningAlgorithm.setFadingFactor(0.9); parameterLearningAlgorithm.setWindowsSize(100); parameterLearningAlgorithm.setOutput(true); parameterLearningAlgorithm.setDataStream(data); parameterLearningAlgorithm.runLearning(); BayesianNetwork bnModel = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bnModel.toString()); }
SVBFadingExample { public static void main(String[] args) throws Exception { DataStream<DataInstance> data = DataStreamLoader.open("datasets/simulated/WasteIncineratorSample.arff"); SVBFading parameterLearningAlgorithm = new SVBFading(); parameterLearningAlgorithm.setDAG(DAGGenerator.getHiddenNaiveBayesStructure(data.getAttributes(),"GlobalHidden", 2)); parameterLearningAlgorithm.setFadingFactor(0.9); parameterLearningAlgorithm.setWindowsSize(100); parameterLearningAlgorithm.setOutput(true); parameterLearningAlgorithm.setDataStream(data); parameterLearningAlgorithm.runLearning(); BayesianNetwork bnModel = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bnModel.toString()); } }
SVBFadingExample { public static void main(String[] args) throws Exception { DataStream<DataInstance> data = DataStreamLoader.open("datasets/simulated/WasteIncineratorSample.arff"); SVBFading parameterLearningAlgorithm = new SVBFading(); parameterLearningAlgorithm.setDAG(DAGGenerator.getHiddenNaiveBayesStructure(data.getAttributes(),"GlobalHidden", 2)); parameterLearningAlgorithm.setFadingFactor(0.9); parameterLearningAlgorithm.setWindowsSize(100); parameterLearningAlgorithm.setOutput(true); parameterLearningAlgorithm.setDataStream(data); parameterLearningAlgorithm.runLearning(); BayesianNetwork bnModel = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bnModel.toString()); }  }
SVBFadingExample { public static void main(String[] args) throws Exception { DataStream<DataInstance> data = DataStreamLoader.open("datasets/simulated/WasteIncineratorSample.arff"); SVBFading parameterLearningAlgorithm = new SVBFading(); parameterLearningAlgorithm.setDAG(DAGGenerator.getHiddenNaiveBayesStructure(data.getAttributes(),"GlobalHidden", 2)); parameterLearningAlgorithm.setFadingFactor(0.9); parameterLearningAlgorithm.setWindowsSize(100); parameterLearningAlgorithm.setOutput(true); parameterLearningAlgorithm.setDataStream(data); parameterLearningAlgorithm.runLearning(); BayesianNetwork bnModel = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bnModel.toString()); }  static void main(String[] args); }
SVBFadingExample { public static void main(String[] args) throws Exception { DataStream<DataInstance> data = DataStreamLoader.open("datasets/simulated/WasteIncineratorSample.arff"); SVBFading parameterLearningAlgorithm = new SVBFading(); parameterLearningAlgorithm.setDAG(DAGGenerator.getHiddenNaiveBayesStructure(data.getAttributes(),"GlobalHidden", 2)); parameterLearningAlgorithm.setFadingFactor(0.9); parameterLearningAlgorithm.setWindowsSize(100); parameterLearningAlgorithm.setOutput(true); parameterLearningAlgorithm.setDataStream(data); parameterLearningAlgorithm.runLearning(); BayesianNetwork bnModel = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bnModel.toString()); }  static void main(String[] args);  }