content: /*
   *
   *
   *    Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements.
   *    See the NOTICE file distributed with this work for additional information regarding copyright ownership.
   *    The ASF licenses this file to You under the Apache License, Version 2.0 (the "License"); you may not use
   *    this file except in compliance with the License.  You may obtain a copy of the License at
   *
   *            http://www.apache.org/licenses/LICENSE-2.0
   *
   *    Unless required by applicable law or agreed to in writing, software distributed under the License is
   *    distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   *    See the License for the specific language governing permissions and limitations under the License.
   *
   *
   */
  
  package eu.amidst.dynamic.examples.models;
  
  import eu.amidst.core.datastream.DataInstance;
  import eu.amidst.core.datastream.DataStream;
  import eu.amidst.dynamic.datastream.DynamicDataInstance;
  import eu.amidst.core.io.DataStreamWriter;
  import eu.amidst.dynamic.io.DynamicDataStreamLoader;
  import eu.amidst.dynamic.learning.parametric.DynamicNaiveBayesClassifier;
  import eu.amidst.core.models.BayesianNetwork;
  import eu.amidst.dynamic.models.DynamicBayesianNetwork;
  import eu.amidst.core.utils.BayesianNetworkGenerator;
  import eu.amidst.core.utils.BayesianNetworkSampler;
  
  import java.io.IOException;
  
  /**
   * Created by andresmasegosa on 15/01/15.
   */
  public class DynamicNaiveBayesClassifierDemo {
      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());
  
  
      }
  }
  