@Test public void test() throws Exception { MLforDBNfromDataset.main(null); }
public static void main(String[] args) throws IOException { DataStream<DynamicDataInstance> data = DynamicDataStreamLoader.loadFromFile( "datasets/simulated/WasteIncineratorSample.arff"); ParameterLearningAlgorithm parallelMaximumLikelihood = new ParallelMaximumLikelihood(); parallelMaximumLikelihood.setWindowsSize(1000); parallelMaximumLikelihood.setDynamicDAG(MLforDBNfromDataset.getNaiveBayesStructure(data.getAttributes(),2)); parallelMaximumLikelihood.initLearning(); parallelMaximumLikelihood.updateModel(data); DynamicBayesianNetwork dbn = parallelMaximumLikelihood.getLearntDBN(); System.out.println(dbn.toString()); }
MLforDBNfromDataset { public static void main(String[] args) throws IOException { DataStream<DynamicDataInstance> data = DynamicDataStreamLoader.loadFromFile( "datasets/simulated/WasteIncineratorSample.arff"); ParameterLearningAlgorithm parallelMaximumLikelihood = new ParallelMaximumLikelihood(); parallelMaximumLikelihood.setWindowsSize(1000); parallelMaximumLikelihood.setDynamicDAG(MLforDBNfromDataset.getNaiveBayesStructure(data.getAttributes(),2)); parallelMaximumLikelihood.initLearning(); parallelMaximumLikelihood.updateModel(data); DynamicBayesianNetwork dbn = parallelMaximumLikelihood.getLearntDBN(); System.out.println(dbn.toString()); } }
MLforDBNfromDataset { public static void main(String[] args) throws IOException { DataStream<DynamicDataInstance> data = DynamicDataStreamLoader.loadFromFile( "datasets/simulated/WasteIncineratorSample.arff"); ParameterLearningAlgorithm parallelMaximumLikelihood = new ParallelMaximumLikelihood(); parallelMaximumLikelihood.setWindowsSize(1000); parallelMaximumLikelihood.setDynamicDAG(MLforDBNfromDataset.getNaiveBayesStructure(data.getAttributes(),2)); parallelMaximumLikelihood.initLearning(); parallelMaximumLikelihood.updateModel(data); DynamicBayesianNetwork dbn = parallelMaximumLikelihood.getLearntDBN(); System.out.println(dbn.toString()); }  }
MLforDBNfromDataset { public static void main(String[] args) throws IOException { DataStream<DynamicDataInstance> data = DynamicDataStreamLoader.loadFromFile( "datasets/simulated/WasteIncineratorSample.arff"); ParameterLearningAlgorithm parallelMaximumLikelihood = new ParallelMaximumLikelihood(); parallelMaximumLikelihood.setWindowsSize(1000); parallelMaximumLikelihood.setDynamicDAG(MLforDBNfromDataset.getNaiveBayesStructure(data.getAttributes(),2)); parallelMaximumLikelihood.initLearning(); parallelMaximumLikelihood.updateModel(data); DynamicBayesianNetwork dbn = parallelMaximumLikelihood.getLearntDBN(); System.out.println(dbn.toString()); }  static DynamicDAG getNaiveBayesStructure(Attributes attributes, int classIndex); static void main(String[] args); }
MLforDBNfromDataset { public static void main(String[] args) throws IOException { DataStream<DynamicDataInstance> data = DynamicDataStreamLoader.loadFromFile( "datasets/simulated/WasteIncineratorSample.arff"); ParameterLearningAlgorithm parallelMaximumLikelihood = new ParallelMaximumLikelihood(); parallelMaximumLikelihood.setWindowsSize(1000); parallelMaximumLikelihood.setDynamicDAG(MLforDBNfromDataset.getNaiveBayesStructure(data.getAttributes(),2)); parallelMaximumLikelihood.initLearning(); parallelMaximumLikelihood.updateModel(data); DynamicBayesianNetwork dbn = parallelMaximumLikelihood.getLearntDBN(); System.out.println(dbn.toString()); }  static DynamicDAG getNaiveBayesStructure(Attributes attributes, int classIndex); static void main(String[] args);  }