Exemplo n.º 1
0
 /**
  * Parameters Constructor
  *
  * @param dataBase Set of training data which is necessary to generate a rule
  * @param train Training data set with information to construct the rule base (mainly, the
  *     training examples)
  */
 public RuleBase(DataBase dataBase, myDataset train) {
   this.ruleBase = new ArrayList<Rule>();
   this.dataBase = dataBase;
   this.train = train;
   this.n_variables = dataBase.numVariables();
   this.fitness = 0;
   this.totalLabels = new int[this.n_variables];
   for (int i = 0; i < this.n_variables; i++) this.totalLabels[i] = dataBase.numLabels(i);
 }
Exemplo n.º 2
0
  /** It launches the algorithm */
  public void execute() {
    if (somethingWrong) { // We do not execute the program
      System.err.println("An error was found, either the data-set has missing values.");
      System.err.println(
          "Please remove the examples with missing data or apply a MV preprocessing.");
      System.err.println("Aborting the program");
      // We should not use the statement: System.exit(-1);
    } else {
      // We do here the algorithm's operations

      nClasses = train.getnClasses();

      dataBase =
          new DataBase(
              train.getnInputs(), train.getRanges(), train.varNames(), train.getNominals());
      Population pobl =
          new Population(
              train,
              dataBase,
              populationSize,
              nRules,
              crossProb,
              ruleWeight,
              combinationType,
              inferenceType,
              p_DC,
              michProb);
      pobl.Generation(this.nGenerations);

      dataBase.writeFile(this.fileDB);
      ruleBase = pobl.bestRB();
      ruleBase.writeFile(this.fileBR);

      // Finally we should fill the training and test output files
      double accTra = doOutput(this.val, this.outputTr);
      double accTst = doOutput(this.test, this.outputTst);

      System.out.println("Accuracy obtained in training: " + accTra);
      System.out.println("Accuracy obtained in test: " + accTst);
      System.out.println("Algorithm Finished");
    }
  }