Package org.apache.uima.ruta.textruler.extension

Examples of org.apache.uima.ruta.textruler.extension.TextRulerLearnerParameter

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    TextRulerLearnerFactory f = algorithmController.getFactory();
    TextRulerLearnerParameter[] params = f.getAlgorithmParameters();
    Map<String, Object> values = f.getAlgorithmParameterStandardValues();
    if (params != null) {
      for (int i = 0; i < params.length; i++) {
        TextRulerLearnerParameter p = params[i];
        String id = algorithmController.getID() + "." + p.id;
        FieldEditor l = null;
        switch (p.type) {
          case ML_BOOL_PARAM: {
            l = new BooleanFieldEditor(id, p.name, top);
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  }

  public TextRulerLearnerParameter[] getAlgorithmParameters() {
    TextRulerLearnerParameter[] result = new TextRulerLearnerParameter[5];

    result[0] = new TextRulerLearnerParameter(BasicLP2.WINDOW_SIZE_KEY,
            "Context Window Size (to the left and right)", MLAlgorithmParamType.ML_INT_PARAM);
    result[1] = new TextRulerLearnerParameter(BasicLP2.CURRENT_BEST_RULES_SIZE_KEY,
            "Best Rules List Size", MLAlgorithmParamType.ML_INT_PARAM);
    result[2] = new TextRulerLearnerParameter(BasicLP2.MIN_COVERED_POSITIVES_PER_RULE_KEY,
            "Minimum Covered Positives per Rule", MLAlgorithmParamType.ML_INT_PARAM);
    result[3] = new TextRulerLearnerParameter(BasicLP2.MAX_ERROR_THRESHOLD_KEY,
            "Maximum Error Threshold", MLAlgorithmParamType.ML_FLOAT_PARAM);
    result[4] = new TextRulerLearnerParameter(BasicLP2.CURRENT_CONTEXTUAL_RULES_SIZE_KEY,
            "Contextual Rules List Size", MLAlgorithmParamType.ML_INT_PARAM);

    return result;
  }
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  }

  public TextRulerLearnerParameter[] getAlgorithmParameters() {
    TextRulerLearnerParameter[] result = new TextRulerLearnerParameter[8];

    result[0] = new TextRulerLearnerParameter(Rapier.COMPRESSION_FAIL_MAX_COUNT_KEY,
            "Maximum Compression Fail Count", MLAlgorithmParamType.ML_INT_PARAM);
    result[1] = new TextRulerLearnerParameter(Rapier.RULELIST_SIZE_KEY, "Internal Rules List Size",
            MLAlgorithmParamType.ML_INT_PARAM);
    result[2] = new TextRulerLearnerParameter(Rapier.PAIR_COUNT_KEY, "Rule Pairs for Generalizing",
            MLAlgorithmParamType.ML_INT_PARAM);
    result[3] = new TextRulerLearnerParameter(Rapier.LIM_NO_IMPROVEMENTS_KEY,
            "Maximum 'No improvement' Count", MLAlgorithmParamType.ML_INT_PARAM);
    result[4] = new TextRulerLearnerParameter(Rapier.NOISE_THESHOLD_KEY, "Maximum Noise Threshold",
            MLAlgorithmParamType.ML_FLOAT_PARAM);
    result[5] = new TextRulerLearnerParameter(Rapier.MIN_COVERED_POSITIVES_KEY,
            "Minimum Covered Positives Per Rule", MLAlgorithmParamType.ML_INT_PARAM);
    result[6] = new TextRulerLearnerParameter(Rapier.POSTAG_ROOTTYPE_KEY, "PosTag Root Type",
            MLAlgorithmParamType.ML_STRING_PARAM);
    result[7] = new TextRulerLearnerParameter(Rapier.USE_ALL_GENSETS_AT_SPECIALIZATION_KEY,
            "Use All 3 GenSets at Specialization", MLAlgorithmParamType.ML_BOOL_PARAM);
    return result;
  }
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  }

  public TextRulerLearnerParameter[] getAlgorithmParameters() {
    TextRulerLearnerParameter[] result = new TextRulerLearnerParameter[3];

    result[0] = new TextRulerLearnerParameter(Whisk.WINDOSIZE_KEY, "Window Size",
            MLAlgorithmParamType.ML_INT_PARAM);
    result[1] = new TextRulerLearnerParameter(Whisk.ERROR_THRESHOLD_KEY, "Maximum Error Threshold",
            MLAlgorithmParamType.ML_FLOAT_PARAM);
    result[2] = new TextRulerLearnerParameter(Whisk.POSTAG_ROOTTYPE_KEY, "PosTag Root Type",
            MLAlgorithmParamType.ML_STRING_PARAM);

    return result;
  }
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    TextRulerLearnerFactory f = algorithmController.getFactory();
    TextRulerLearnerParameter[] params = f.getAlgorithmParameters();
    Map<String, Object> values = f.getAlgorithmParameterStandardValues();
    if (params != null) {
      for (int i = 0; i < params.length; i++) {
        TextRulerLearnerParameter p = params[i];
        String id = algorithmController.getID() + "." + p.id;
        FieldEditor l = null;
        switch (p.type) {
          case ML_BOOL_PARAM: {
            l = new BooleanFieldEditor(id, p.name, top);
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    TextRulerLearnerFactory f = algorithmController.getFactory();
    TextRulerLearnerParameter[] params = f.getAlgorithmParameters();
    Map<String, Object> values = f.getAlgorithmParameterStandardValues();
    if (params != null) {
      for (int i = 0; i < params.length; i++) {
        TextRulerLearnerParameter p = params[i];
        String id = algorithmController.getID() + "." + p.id;
        FieldEditor l = null;
        switch (p.type) {
          case ML_BOOL_PARAM: {
            l = new BooleanFieldEditor(id, p.name, getFieldEditorParent());
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            tempFolderPath, fullSlotTypeNames, filterSet, skip, delegate);
  }

  public TextRulerLearnerParameter[] getAlgorithmParameters() {
    TextRulerLearnerParameter[] result = new TextRulerLearnerParameter[6];
    result[0] = new TextRulerLearnerParameter(TrabalLearner.ALGORITHM_ITERATIONS_KEY,
            "Number of times, the algorithm iterates.", MLAlgorithmParamType.ML_INT_PARAM);
    result[1] = new TextRulerLearnerParameter(TrabalLearner.MAX_NUMBER_OF_BASIC_RULES_KEY,
            "Number of basic rules to be created for one example.",
            MLAlgorithmParamType.ML_INT_PARAM);
    result[2] = new TextRulerLearnerParameter(TrabalLearner.MAX_NUMBER_OF_RULES_KEY,
            "Number of optimized rules to be created for one example.",
            MLAlgorithmParamType.ML_INT_PARAM);
    result[3] = new TextRulerLearnerParameter(TrabalLearner.MAX_NUMBER_OF_ITERATIONS_KEY,
            "Maximum number of iterations, when optimizing rules.",
            MLAlgorithmParamType.ML_INT_PARAM);
    result[4] = new TextRulerLearnerParameter(TrabalLearner.MAX_ERROR_RATE_KEY,
            "Maximum allowed error rate.", MLAlgorithmParamType.ML_DOUBLE_PARAM);
    result[5] = new TextRulerLearnerParameter(TrabalLearner.ENABLE_FEATURES_KEY,
            "Correct features in rules and conditions.", MLAlgorithmParamType.ML_BOOL_PARAM);
    return result;
  }
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    TextRulerLearnerFactory f = algorithmController.getFactory();
    TextRulerLearnerParameter[] params = f.getAlgorithmParameters();
    Map<String, Object> values = f.getAlgorithmParameterStandardValues();
    if (params != null) {
      for (int i = 0; i < params.length; i++) {
        TextRulerLearnerParameter p = params[i];
        String id = algorithmController.getID() + "." + p.id;
        FieldEditor l = null;
        switch (p.type) {
          case ML_BOOL_PARAM: {
            l = new BooleanFieldEditor(id, p.name, getFieldEditorParent());
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  }

  public TextRulerLearnerParameter[] getAlgorithmParameters() {
    TextRulerLearnerParameter[] result = new TextRulerLearnerParameter[5];

    result[0] = new TextRulerLearnerParameter(BasicLP2.WINDOW_SIZE_KEY,
            "Context Window Size (to the left and right)", MLAlgorithmParamType.ML_INT_PARAM);
    result[1] = new TextRulerLearnerParameter(BasicLP2.CURRENT_BEST_RULES_SIZE_KEY,
            "Best Rules List Size", MLAlgorithmParamType.ML_INT_PARAM);
    result[2] = new TextRulerLearnerParameter(BasicLP2.MIN_COVERED_POSITIVES_PER_RULE_KEY,
            "Minimum Covered Positives per Rule", MLAlgorithmParamType.ML_INT_PARAM);
    result[3] = new TextRulerLearnerParameter(BasicLP2.MAX_ERROR_THRESHOLD_KEY,
            "Maximum Error Threshold", MLAlgorithmParamType.ML_FLOAT_PARAM);
    result[4] = new TextRulerLearnerParameter(BasicLP2.CURRENT_CONTEXTUAL_RULES_SIZE_KEY,
            "Contextual Rules List Size", MLAlgorithmParamType.ML_INT_PARAM);

    return result;
  }
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    TextRulerLearnerFactory f = algorithmController.getFactory();
    TextRulerLearnerParameter[] params = f.getAlgorithmParameters();
    Map<String, Object> values = f.getAlgorithmParameterStandardValues();
    if (params != null) {
      for (int i = 0; i < params.length; i++) {
        TextRulerLearnerParameter p = params[i];
        String id = algorithmController.getID() + "." + p.id;
        FieldEditor l = null;
        switch (p.type) {
          case ML_BOOL_PARAM: {
            l = new BooleanFieldEditor(id, p.name, getFieldEditorParent());
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Related Classes of org.apache.uima.ruta.textruler.extension.TextRulerLearnerParameter

  • org.apache.uima.ruta.textruler.learner.kep.KEPFactory
  • org.apache.uima.ruta.textruler.learner.kep.KEPPreferencePage
  • org.apache.uima.ruta.textruler.learner.lp2.NaiveLP2Factory
  • org.apache.uima.ruta.textruler.learner.lp2.NaiveLP2PreferencePage
  • org.apache.uima.ruta.textruler.learner.lp2.OptimizedLP2Factory
  • org.apache.uima.ruta.textruler.learner.lp2.OptimizedLP2PreferencePage
  • org.apache.uima.ruta.textruler.learner.rapier.RapierFactory
  • org.apache.uima.ruta.textruler.learner.rapier.RapierPreferencePage
  • org.apache.uima.ruta.textruler.learner.trabal.TrabalFactory
  • org.apache.uima.ruta.textruler.learner.trabal.TrabalPreferencePage
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