/** * Main method for testing this class. * * @param argv should contain a sequence of numeric values */ public static void main(String[] argv) { try { if (argv.length == 0) { System.out.println("Please specify a set of instances."); return; } NormalEstimator newEst = new NormalEstimator(0.01); for (int i = 0; i < argv.length; i++) { double current = Double.valueOf(argv[i]).doubleValue(); System.out.println(newEst); System.out.println("Prediction for " + current + " = " + newEst.getProbability(current)); newEst.addValue(current, 1); } NormalEstimator.testAggregation(); } catch (Exception e) { System.out.println(e.getMessage()); } } }
/** * Main method for testing this class. * * @param argv should contain a sequence of numeric values */ public static void main(String[] argv) { try { if (argv.length == 0) { System.out.println("Please specify a set of instances."); return; } NormalEstimator newEst = new NormalEstimator(0.01); for (int i = 0; i < argv.length; i++) { double current = Double.valueOf(argv[i]).doubleValue(); System.out.println(newEst); System.out.println("Prediction for " + current + " = " + newEst.getProbability(current)); newEst.addValue(current, 1); } NormalEstimator.testAggregation(); } catch (Exception e) { System.out.println(e.getMessage()); } } }
public static void testAggregation() { NormalEstimator ne = new NormalEstimator(0.01); NormalEstimator one = new NormalEstimator(0.01); NormalEstimator two = new NormalEstimator(0.01); java.util.Random r = new java.util.Random(1); for (int i = 0; i < 100; i++) { double z = r.nextDouble(); ne.addValue(z, 1); if (i < 50) { one.addValue(z, 1); } else { two.addValue(z, 1); } } try { System.out.println("\n\nFull\n"); System.out.println(ne.toString()); System.out.println("Prob (0): " + ne.getProbability(0)); System.out.println("\nOne\n" + one.toString()); System.out.println("Prob (0): " + one.getProbability(0)); System.out.println("\nTwo\n" + two.toString()); System.out.println("Prob (0): " + two.getProbability(0)); one = one.aggregate(two); System.out.println("\nAggregated\n"); System.out.println(one.toString()); System.out.println("Prob (0): " + one.getProbability(0)); } catch (Exception ex) { ex.printStackTrace(); } }
public static void testAggregation() { NormalEstimator ne = new NormalEstimator(0.01); NormalEstimator one = new NormalEstimator(0.01); NormalEstimator two = new NormalEstimator(0.01); java.util.Random r = new java.util.Random(1); for (int i = 0; i < 100; i++) { double z = r.nextDouble(); ne.addValue(z, 1); if (i < 50) { one.addValue(z, 1); } else { two.addValue(z, 1); } } try { System.out.println("\n\nFull\n"); System.out.println(ne.toString()); System.out.println("Prob (0): " + ne.getProbability(0)); System.out.println("\nOne\n" + one.toString()); System.out.println("Prob (0): " + one.getProbability(0)); System.out.println("\nTwo\n" + two.toString()); System.out.println("Prob (0): " + two.getProbability(0)); one = one.aggregate(two); System.out.println("\nAggregated\n"); System.out.println(one.toString()); System.out.println("Prob (0): " + one.getProbability(0)); } catch (Exception ex) { ex.printStackTrace(); } }
/** * Get a probability estimator for a value * * @param given the new value that data is conditional upon * @return the estimator for the supplied value given the condition */ public Estimator getEstimator(double given) { Estimator result = new DiscreteEstimator(m_Estimators.length,false); for(int i = 0; i < m_Estimators.length; i++) { result.addValue(i,m_Weights.getProbability(i) *m_Estimators[i].getProbability(given)); } return result; }
/** * Get a probability estimator for a value * * @param given the new value that data is conditional upon * @return the estimator for the supplied value given the condition */ public Estimator getEstimator(double given) { Estimator result = new DiscreteEstimator(m_Estimators.length,false); for(int i = 0; i < m_Estimators.length; i++) { result.addValue(i,m_Weights.getProbability(i) *m_Estimators[i].getProbability(given)); } return result; }