private void SaveCrossValidationAssignments() throws Exception {
    String outerFoldsFilePath =
        Settings.GetOutputSettingsDir(true) + "Validation_Assignments_for_Outer_Folds.txt";

    FileUtilities.WriteTextToFile(
        outerFoldsFilePath,
        "# The outer cross-validation fold to which each data instance was assigned.\n");
    FileUtilities.AppendTextToFile(
        outerFoldsFilePath, Singletons.InstanceVault.GetCrossValidationAssignments().toString());

    if (Singletons.InstanceVault.GetCrossValidationAssignments().NumFolds
        != Singletons.InstanceVault.TransformedDependentVariableInstances.Size())
      for (int outerFold :
          Singletons.InstanceVault.GetCrossValidationAssignments().GetAllFoldNumbers()) {
        String innerFoldFilePath =
            Settings.GetOutputSettingsDir(true)
                + "Validation_Assignments_for_Inner_Folds_in_OuterFold_"
                + outerFold
                + ".txt";
        FileUtilities.WriteTextToFile(
            innerFoldFilePath,
            "# The inner cross-validation fold (within outer fold "
                + outerFold
                + ") to which data instances were assigned.\n");
        FileUtilities.AppendTextToFile(
            innerFoldFilePath,
            Singletons.InstanceVault.GetCrossValidationAssignments()
                .GetInnerAssignments(outerFold)
                .toString());
      }
  }
 private void SaveExcludedTrainingIDInfo() throws Exception {
   ArrayList<String> excludedTrainingIDs =
       Singletons.InstanceVault.GetCrossValidationAssignments().GetAllExcludedTrainIDs();
   if (excludedTrainingIDs.size() > 0) {
     String filePath = Settings.GetOutputSettingsDir(true) + "Excluded_Training_IDs.txt";
     String output = ListUtilities.Join(excludedTrainingIDs, "\n");
     FileUtilities.WriteLineToFile(
         filePath,
         "# IDs of data instances that were excluded randomly from training sets, according to the specified experiment settings. If this is a cross-validation experiment, the instances were removed from different folds.");
     FileUtilities.AppendLineToFile(filePath, output);
   }
 }
示例#3
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  /**
   * Depending on the settings for the experiment and the current iteration, this method returns a
   * path to where the settings files should be saved.
   *
   * @param appendIterationIfMoreThanOne Whether to append the iteration number if more than one
   *     iteration is being executed
   * @return Path to where the settings files should be saved
   * @throws Exception
   */
  public static String GetOutputSettingsDir(boolean appendIterationIfMoreThanOne) throws Exception {
    String dirPath = Settings.OUTPUT_DIR + "Settings/";

    if (Singletons.Config.GetNumIterations() > 1 && appendIterationIfMoreThanOne)
      dirPath += "Iteration" + Singletons.Iteration + "/";

    return FileUtilities.CreateDirectoryIfNotExists(dirPath);
  }
示例#4
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  /**
   * The purpose of this method is to parse the information that is listed in the learners
   * configuration file.
   *
   * @throws Exception
   */
  public static void ParseLearners() throws Exception {
    for (String line : FileUtilities.ReadLinesFromFile(LEARNER_TEMPLATES_FILE)) {
      if (line.startsWith("#") || line.trim().length() == 0) // Ignore comment characters
      continue;

      ArrayList<String> lineItems = ListUtilities.CreateStringList(line.split(";"));
      String description = lineItems.get(0);
      String learnerClassName = lineItems.get(1);
      String commandTemplate = (lineItems.size() > 2) ? lineItems.get(2) : "";

      LearnerConfigMap.put(
          description, new LearnerConfig(description, learnerClassName, commandTemplate));
    }
  }
示例#5
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  /**
   * The purpose of this method is to parse the algorithms that have been defined in the algorithm
   * configuration files.
   *
   * @throws Exception
   */
  public static void ParseAlgorithms() throws Exception {
    for (String line : FileUtilities.ReadLinesFromFile(CLASSIFICATION_ALGORITHMS_FILE)) {
      if (line.startsWith("#") || line.trim().length() == 0) // Ignore comment characters
      continue;

      ArrayList<String> lineItems = ListUtilities.CreateStringList(line.split(";"));
      String key = lineItems.remove(0);
      String learnerKey = lineItems.remove(0);

      CheckLearnerKey(key, learnerKey);
      ClassificationAlgorithms.put(key, new ClassificationAlgorithm(key, learnerKey, lineItems));
    }

    for (String line : FileUtilities.ReadLinesFromFile(FEATURE_SELECTION_ALGORITHMS_FILE)) {
      if (line.startsWith("#") || line.trim().length() == 0) // Ignore comment characters
      continue;

      ArrayList<String> lineItems = ListUtilities.CreateStringList(line.split(";"));

      String key = lineItems.remove(0);
      String learnerKey = lineItems.remove(0);
      ArrayList<String> parameters = lineItems;

      CheckLearnerKey(key, learnerKey);
      FeatureSelectionAlgorithms.put(
          key, new FeatureSelectionAlgorithm(key, learnerKey, parameters));
    }

    // The following algorithms are made available to any experiment and aren't specified in the
    // config file
    FeatureSelectionAlgorithms.put(
        "None", new FeatureSelectionAlgorithm("None", "", new ArrayList<String>()));
    FeatureSelectionAlgorithms.put(
        "PriorKnowledge",
        new FeatureSelectionAlgorithm("PriorKnowledge", "", new ArrayList<String>()));
  }
  /**
   * Executes a series of tasks that are "locked" such that only one thread should execute each.
   * These are locked across multiple compute nodes as well.
   *
   * @param description Name of the series of tasks that will be executed
   * @param lockedCallables Tasks that will be executed
   * @throws Exception
   */
  public static void ExecuteLockTasks(String description, ArrayList<LockedCallable> lockedCallables)
      throws Exception {
    MultiThreadedTaskHandler taskHandler = new MultiThreadedTaskHandler(description);

    // Prepare the tasks to be executed
    for (LockedCallable callable : lockedCallables) {
      FileUtilities.CreateFileDirectoryIfNotExists(callable.StatusFilePath);
      taskHandler.Add(callable);
    }

    try {
      // See if any of the tasks returned a false value and if so, pause then retry
      if (ListUtilities.AnyFalse(ListUtilities.CreateBooleanList(taskHandler.Execute()))) {
        Pause(description);
        ExecuteLockTasks(description, lockedCallables);
      }
    } catch (Exception ex) {
      // If an exception occurred, log it, pause, then try again
      Singletons.Log.Exception(ex);
      Pause(description);
      ExecuteLockTasks(description, lockedCallables);
    }
  }
  /**
   * This method saves various description files to the output. These tasks are quick to execute, so
   * they are grouped together rather than parallelized.
   *
   * @throws Exception
   */
  public void SaveExperimentDescriptionFiles() throws Exception {
    // Save the version file in output so people know which version was used
    FileUtilities.CopyFile(
        Settings.VERSION_FILE, Settings.GetOutputSettingsDir(false) + Settings.VERSION_FILE);

    // Copy the experiment file
    FileUtilities.WriteLineToFile(
        Settings.GetOutputSettingsDir(false) + "Experiment_Settings.txt",
        "# All settings used in this experiment, whether explicitly set or used by default in the absence of an explicit setting");
    FileUtilities.AppendTextToFile(
        Settings.GetOutputSettingsDir(false) + "Experiment_Settings.txt",
        Singletons.Config.toString());

    if (Settings.NeedToClassify()) {
      // Copy the algorithm configuration files
      FileUtilities.CopyFile(
          Settings.LEARNER_TEMPLATES_FILE,
          Settings.GetOutputSettingsDir(false)
              + new File(Settings.LEARNER_TEMPLATES_FILE).getName());

      // Copy the algorithm configuration files
      FileUtilities.CopyFile(
          Settings.CLASSIFICATION_ALGORITHMS_FILE,
          Settings.GetOutputSettingsDir(false)
              + new File(Settings.CLASSIFICATION_ALGORITHMS_FILE).getName());

      if (Settings.NeedToSelectFeatures())
        FileUtilities.CopyFile(
            Settings.FEATURE_SELECTION_ALGORITHMS_FILE,
            Settings.GetOutputSettingsDir(false)
                + new File(Settings.FEATURE_SELECTION_ALGORITHMS_FILE).getName());

      SaveExcludedTrainingIDInfo();
      SaveCrossValidationAssignments();
    }
  }
示例#8
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 /**
  * Depending on the settings for the experiment, this method returns a path to where the
  * statistics files should be saved.
  *
  * @return Path to where the statistics files should be saved
  * @throws Exception
  */
 public static String GetOutputStatisticsDir() throws Exception {
   return FileUtilities.CreateDirectoryIfNotExists(Settings.OUTPUT_DIR + "Statistics/");
 }