@Test public void test() throws Exception { NaiveBayesVirtualConceptDriftDetectorExample.main(null); }
public static void main(String[] args) { DataStream<DataInstance> data = DataStreamLoader.open("./datasets/DriftSets/sea.arff"); NaiveBayesVirtualConceptDriftDetector virtualDriftDetector = new NaiveBayesVirtualConceptDriftDetector(); virtualDriftDetector.setClassIndex(-1); virtualDriftDetector.setData(data); int windowSize = 1000; virtualDriftDetector.setWindowsSize(windowSize); virtualDriftDetector.setTransitionVariance(0.1); virtualDriftDetector.setNumberOfGlobalVars(1); virtualDriftDetector.initLearning(); System.out.print("Batch"); for (Variable hiddenVar : virtualDriftDetector.getHiddenVars()) { System.out.print("\t" + hiddenVar.getName()); } System.out.println(); int countBatch = 0; for (DataOnMemory<DataInstance> batch : data.iterableOverBatches(windowSize)){ double[] out = virtualDriftDetector.updateModel(batch); System.out.print(countBatch + "\t"); for (int i = 0; i < out.length; i++) { System.out.print(out[i]+"\t"); } System.out.println(); countBatch++; } }
NaiveBayesVirtualConceptDriftDetectorExample { public static void main(String[] args) { DataStream<DataInstance> data = DataStreamLoader.open("./datasets/DriftSets/sea.arff"); NaiveBayesVirtualConceptDriftDetector virtualDriftDetector = new NaiveBayesVirtualConceptDriftDetector(); virtualDriftDetector.setClassIndex(-1); virtualDriftDetector.setData(data); int windowSize = 1000; virtualDriftDetector.setWindowsSize(windowSize); virtualDriftDetector.setTransitionVariance(0.1); virtualDriftDetector.setNumberOfGlobalVars(1); virtualDriftDetector.initLearning(); System.out.print("Batch"); for (Variable hiddenVar : virtualDriftDetector.getHiddenVars()) { System.out.print("\t" + hiddenVar.getName()); } System.out.println(); int countBatch = 0; for (DataOnMemory<DataInstance> batch : data.iterableOverBatches(windowSize)){ double[] out = virtualDriftDetector.updateModel(batch); System.out.print(countBatch + "\t"); for (int i = 0; i < out.length; i++) { System.out.print(out[i]+"\t"); } System.out.println(); countBatch++; } } }
NaiveBayesVirtualConceptDriftDetectorExample { public static void main(String[] args) { DataStream<DataInstance> data = DataStreamLoader.open("./datasets/DriftSets/sea.arff"); NaiveBayesVirtualConceptDriftDetector virtualDriftDetector = new NaiveBayesVirtualConceptDriftDetector(); virtualDriftDetector.setClassIndex(-1); virtualDriftDetector.setData(data); int windowSize = 1000; virtualDriftDetector.setWindowsSize(windowSize); virtualDriftDetector.setTransitionVariance(0.1); virtualDriftDetector.setNumberOfGlobalVars(1); virtualDriftDetector.initLearning(); System.out.print("Batch"); for (Variable hiddenVar : virtualDriftDetector.getHiddenVars()) { System.out.print("\t" + hiddenVar.getName()); } System.out.println(); int countBatch = 0; for (DataOnMemory<DataInstance> batch : data.iterableOverBatches(windowSize)){ double[] out = virtualDriftDetector.updateModel(batch); System.out.print(countBatch + "\t"); for (int i = 0; i < out.length; i++) { System.out.print(out[i]+"\t"); } System.out.println(); countBatch++; } }  }
NaiveBayesVirtualConceptDriftDetectorExample { public static void main(String[] args) { DataStream<DataInstance> data = DataStreamLoader.open("./datasets/DriftSets/sea.arff"); NaiveBayesVirtualConceptDriftDetector virtualDriftDetector = new NaiveBayesVirtualConceptDriftDetector(); virtualDriftDetector.setClassIndex(-1); virtualDriftDetector.setData(data); int windowSize = 1000; virtualDriftDetector.setWindowsSize(windowSize); virtualDriftDetector.setTransitionVariance(0.1); virtualDriftDetector.setNumberOfGlobalVars(1); virtualDriftDetector.initLearning(); System.out.print("Batch"); for (Variable hiddenVar : virtualDriftDetector.getHiddenVars()) { System.out.print("\t" + hiddenVar.getName()); } System.out.println(); int countBatch = 0; for (DataOnMemory<DataInstance> batch : data.iterableOverBatches(windowSize)){ double[] out = virtualDriftDetector.updateModel(batch); System.out.print(countBatch + "\t"); for (int i = 0; i < out.length; i++) { System.out.print(out[i]+"\t"); } System.out.println(); countBatch++; } }  static void main(String[] args); }
NaiveBayesVirtualConceptDriftDetectorExample { public static void main(String[] args) { DataStream<DataInstance> data = DataStreamLoader.open("./datasets/DriftSets/sea.arff"); NaiveBayesVirtualConceptDriftDetector virtualDriftDetector = new NaiveBayesVirtualConceptDriftDetector(); virtualDriftDetector.setClassIndex(-1); virtualDriftDetector.setData(data); int windowSize = 1000; virtualDriftDetector.setWindowsSize(windowSize); virtualDriftDetector.setTransitionVariance(0.1); virtualDriftDetector.setNumberOfGlobalVars(1); virtualDriftDetector.initLearning(); System.out.print("Batch"); for (Variable hiddenVar : virtualDriftDetector.getHiddenVars()) { System.out.print("\t" + hiddenVar.getName()); } System.out.println(); int countBatch = 0; for (DataOnMemory<DataInstance> batch : data.iterableOverBatches(windowSize)){ double[] out = virtualDriftDetector.updateModel(batch); System.out.print(countBatch + "\t"); for (int i = 0; i < out.length; i++) { System.out.print(out[i]+"\t"); } System.out.println(); countBatch++; } }  static void main(String[] args);  }