@Test public void test() throws Exception { MaximumLikelihoodLearningExample.main(null); }
public static void main(String[] args) throws Exception { SparkConf conf = new SparkConf().setAppName("SparkLink!").setMaster("local");; SparkContext sc = new SparkContext(conf); SQLContext sqlContext = new SQLContext(sc); String path ="datasets/simulated/WI_samples.json"; DataSpark dataSpark = DataSparkLoader.open(sqlContext, path); ParallelMaximumLikelihood parameterLearningAlgorithm = new ParallelMaximumLikelihood(); DAG dag = DAGGenerator.getNaiveBayesStructure(dataSpark.getAttributes(), "W"); parameterLearningAlgorithm.setDAG(dag); parameterLearningAlgorithm.setBatchSize(100); parameterLearningAlgorithm.setDataSpark(dataSpark); parameterLearningAlgorithm.runLearning(); BayesianNetwork bn = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bn); }
MaximumLikelihoodLearningExample { public static void main(String[] args) throws Exception { SparkConf conf = new SparkConf().setAppName("SparkLink!").setMaster("local");; SparkContext sc = new SparkContext(conf); SQLContext sqlContext = new SQLContext(sc); String path ="datasets/simulated/WI_samples.json"; DataSpark dataSpark = DataSparkLoader.open(sqlContext, path); ParallelMaximumLikelihood parameterLearningAlgorithm = new ParallelMaximumLikelihood(); DAG dag = DAGGenerator.getNaiveBayesStructure(dataSpark.getAttributes(), "W"); parameterLearningAlgorithm.setDAG(dag); parameterLearningAlgorithm.setBatchSize(100); parameterLearningAlgorithm.setDataSpark(dataSpark); parameterLearningAlgorithm.runLearning(); BayesianNetwork bn = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bn); } }
MaximumLikelihoodLearningExample { public static void main(String[] args) throws Exception { SparkConf conf = new SparkConf().setAppName("SparkLink!").setMaster("local");; SparkContext sc = new SparkContext(conf); SQLContext sqlContext = new SQLContext(sc); String path ="datasets/simulated/WI_samples.json"; DataSpark dataSpark = DataSparkLoader.open(sqlContext, path); ParallelMaximumLikelihood parameterLearningAlgorithm = new ParallelMaximumLikelihood(); DAG dag = DAGGenerator.getNaiveBayesStructure(dataSpark.getAttributes(), "W"); parameterLearningAlgorithm.setDAG(dag); parameterLearningAlgorithm.setBatchSize(100); parameterLearningAlgorithm.setDataSpark(dataSpark); parameterLearningAlgorithm.runLearning(); BayesianNetwork bn = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bn); }  }
MaximumLikelihoodLearningExample { public static void main(String[] args) throws Exception { SparkConf conf = new SparkConf().setAppName("SparkLink!").setMaster("local");; SparkContext sc = new SparkContext(conf); SQLContext sqlContext = new SQLContext(sc); String path ="datasets/simulated/WI_samples.json"; DataSpark dataSpark = DataSparkLoader.open(sqlContext, path); ParallelMaximumLikelihood parameterLearningAlgorithm = new ParallelMaximumLikelihood(); DAG dag = DAGGenerator.getNaiveBayesStructure(dataSpark.getAttributes(), "W"); parameterLearningAlgorithm.setDAG(dag); parameterLearningAlgorithm.setBatchSize(100); parameterLearningAlgorithm.setDataSpark(dataSpark); parameterLearningAlgorithm.runLearning(); BayesianNetwork bn = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bn); }  static void main(String[] args); }
MaximumLikelihoodLearningExample { public static void main(String[] args) throws Exception { SparkConf conf = new SparkConf().setAppName("SparkLink!").setMaster("local");; SparkContext sc = new SparkContext(conf); SQLContext sqlContext = new SQLContext(sc); String path ="datasets/simulated/WI_samples.json"; DataSpark dataSpark = DataSparkLoader.open(sqlContext, path); ParallelMaximumLikelihood parameterLearningAlgorithm = new ParallelMaximumLikelihood(); DAG dag = DAGGenerator.getNaiveBayesStructure(dataSpark.getAttributes(), "W"); parameterLearningAlgorithm.setDAG(dag); parameterLearningAlgorithm.setBatchSize(100); parameterLearningAlgorithm.setDataSpark(dataSpark); parameterLearningAlgorithm.runLearning(); BayesianNetwork bn = parameterLearningAlgorithm.getLearntBayesianNetwork(); System.out.println(bn); }  static void main(String[] args);  }