コード例 #1
0
ファイル: Prism.java プロジェクト: Navieclipse/KEEL
  /** Creates the total selector's set for get all the possible rules */
  private Complejo hazSelectores(Dataset train) {

    Complejo almacenSelectores;
    int nClases = train.getnclases();
    almacenSelectores =
        new Complejo(nClases); // Aqui voy a almacenar los selectores (numVariable,operador,valor)
    Attribute[] atributos = null;
    int num_atributos, type;
    Vector nominalValues;
    atributos = Attributes.getAttributes();
    num_atributos = Attributes.getNumAttributes();
    Selector s;

    for (int i = 0; i < train.getnentradas(); i++) {
      type = atributos[i].getType();
      switch (type) {
        case 0: // NOMINAL
          nominalValues = atributos[i].getNominalValuesList();
          // System.out.print("{");
          for (int j = 0; j < nominalValues.size(); j++) {
            // System.out.print ((String)nominalValues.elementAt(j)+"  ");
            s = new Selector(i, 0, (String) nominalValues.elementAt(j), true); // [atr,op,valor]
            // incluimos tb los valores en double para facilitar algunas funciones
            s.setValor((double) j);
            almacenSelectores.addSelector(s);
            // s.print();
          }
          // System.out.println("}");
          break;
      }
      // System.out.println(num_atributos);
    }
    return almacenSelectores;
  }
コード例 #2
0
ファイル: InstanceSet.java プロジェクト: Navieclipse/KEEL
  /** It does return the original header definiton but without @input and @output in there */
  public String getOriginalHeaderWithoutInOut() {
    String line = "";
    Attribute[] attrs = null;

    // Getting the relation name and the attributes
    if (storeAttributesAsNonStatic && attributes != null) {
      line = "@relation " + attributes.getRelationName() + "\n";
      attrs = attributes.getAttributes();
    } else {
      line = "@relation " + Attributes.getRelationName() + "\n";
      attrs = Attributes.getAttributes();
    }

    for (int i = 0; i < attrs.length; i++) {
      line += attrs[i].toString() + "\n";
    }
    return line;
  } // end getOriginalHeaderWithoutInOut
コード例 #3
0
ファイル: Dataset.java プロジェクト: Navieclipse/KEEL
  /**
   * It reads the whole input data-set and it stores each example and its associated output value in
   * local arrays to ease their use.
   *
   * @param datasetFile String name of the file containing the dataset
   * @param train boolean It must have the value "true" if we are reading the training data-set
   * @throws IOException If there ocurs any problem with the reading of the data-set
   */
  public void readClassificationSet(String datasetFile, boolean train) throws IOException {
    try {
      // Load in memory a dataset that contains a classification problem
      IS.readSet(datasetFile, train);
      nData = IS.getNumInstances();
      nInputs = Attributes.getInputNumAttributes();
      nVars = nInputs + Attributes.getOutputNumAttributes();

      // outputIntegerheck that there is only one output variable
      if (Attributes.getOutputNumAttributes() > 1) {
        System.out.println("This algorithm can not process MIMO datasets");
        System.out.println("All outputs but the first one will be removed");
        System.exit(1);
      }
      boolean noOutputs = false;
      if (Attributes.getOutputNumAttributes() < 1) {
        System.out.println("This algorithm can not process datasets without outputs");
        System.out.println("Zero-valued output generated");
        noOutputs = true;
        System.exit(1);
      }

      // Initialice and fill our own tables
      X = new double[nData][nInputs];
      Nominal = new String[nData][nVars];
      missing = new boolean[nData][nVars];
      outputInteger = new int[nData];
      outputReal = new double[nData];
      output = new String[nData];

      // Maximum and minimum of inputs
      emax = new double[nInputs];
      emin = new double[nInputs];
      for (int i = 0; i < nInputs; i++) {
        emax[i] = Attributes.getAttribute(i).getMaxAttribute();
        emin[i] = Attributes.getAttribute(i).getMinAttribute();
      }
      // All values are casted into double/integer
      nClasses = 0;
      for (int i = 0; i < nData; i++) {
        Instance inst = IS.getInstance(i);
        for (int j = 0; j < nInputs; j++) {
          X[i][j] = IS.getInputNumericValue(i, j); // inst.getInputRealValues(j);
          Nominal[i][j] = "" + IS.getInputNumericValue(i, j);
          missing[i][j] = inst.getInputMissingValues(j);
          if (missing[i][j]) {
            X[i][j] = emin[j] - 1;
          }
        }

        if (noOutputs) {
          outputInteger[i] = 0;
          output[i] = "";
        } else {
          outputInteger[i] = (int) IS.getOutputNumericValue(i, 0);
          output[i] = IS.getOutputNominalValue(i, 0);
          Nominal[i][nInputs] = output[i];
          missing[i][nInputs] = false;
        }
        if (outputInteger[i] > nClasses) {
          nClasses = outputInteger[i];
        }
      }
      nClasses++;
      System.out.println("Number of classes=" + nClasses);

    } catch (Exception e) {
      System.out.println("DBG: Exception in readSet");
      e.printStackTrace();
    }
    computeStatistics();
    this.computeInstancesPerClass();
    Attribute[] atts = Attributes.getAttributes();
    for (indexClass = 0;
        (indexClass < atts.length)
            && (!(Attributes.getOutputAttribute(0)
                .getName()
                .equalsIgnoreCase(atts[indexClass].getName())));
        indexClass++) {;
    }
  }