BayesianNetworkGenerator.setSeed(0); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2);
BayesianNetworkGenerator.setNumberOfGaussianVars(10); BayesianNetworkGenerator.setNumberOfMultinomialVars(10, 5); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2); System.out.println(bn.toString());
BayesianNetworkGenerator.setSeed(0); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2);
BayesianNetworkGenerator.setSeed(0); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2); BayesianNetworkSampler sampler = new BayesianNetworkSampler(bn); DataStream<DataInstance> dataStream = sampler.sampleToDataStream(sampleSize);
BayesianNetworkGenerator.setSeed(0); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2);
public static void main(String[] args) throws IOException { BayesianNetworkGenerator.setNumberOfGaussianVars(0); BayesianNetworkGenerator.setNumberOfMultinomialVars(5, 3); BayesianNetworkGenerator.setSeed(0); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2); int sampleSize = 1000000; BayesianNetworkSampler sampler = new BayesianNetworkSampler(bn); String file = "./datasets/simulated/randomdata.arff"; DataStream<DataInstance> dataStream = sampler.sampleToDataStream(sampleSize); DataStreamWriter.writeDataToFile(dataStream, file); DataStream<DynamicDataInstance> data = DynamicDataStreamLoader.loadFromFile(file); DynamicNaiveBayesClassifier model = new DynamicNaiveBayesClassifier(); model.setClassVarID(data.getAttributes().getNumberOfAttributes() - 1); model.setParallelMode(true); model.learn(data); DynamicBayesianNetwork nbClassifier = model.getDynamicBNModel(); System.out.println(nbClassifier.toString()); } }
public static void main(String[] args) throws IOException { BayesianNetworkGenerator.setNumberOfGaussianVars(0); BayesianNetworkGenerator.setNumberOfMultinomialVars(5, 2); BayesianNetworkGenerator.setSeed(0); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2); int sampleSize = 1000; BayesianNetworkSampler sampler = new BayesianNetworkSampler(bn); String file = "./datasets/simulated/randomdata.arff"; DataStream<DataInstance> dataStream = sampler.sampleToDataStream(sampleSize); DataStreamWriter.writeDataToFile(dataStream, file); DataStream<DynamicDataInstance> data = DynamicDataStreamLoader.loadFromFile(file); for (int i = 1; i <= 1; i++) { DynamicNaiveBayesClassifier model = new DynamicNaiveBayesClassifier(); model.setClassVarID(data.getAttributes().getNumberOfAttributes() - 1); model.setParallelMode(true); model.learn(data); DynamicBayesianNetwork nbClassifier = model.getDynamicBNModel(); System.out.println(nbClassifier.toString()); } } }
BayesianNetworkGenerator.setNumberOfMultinomialVars(numDiscVars, numStates); BayesianNetworkGenerator.setSeed(0); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2);
BayesianNetworkGenerator.setNumberOfGaussianVars(2); BayesianNetwork bn = BayesianNetworkGenerator.generateNaiveBayes(2);