Esempio n. 1
0
  private void processExamples(String group, List<Example> examples) {
    Evaluation evaluation = new Evaluation();
    if (examples.isEmpty()) return;

    final String prefix = "iter=0." + group;
    Execution.putOutput("group", group);
    LogInfo.begin_track_printAll("Processing %s: %s examples", prefix, examples.size());
    LogInfo.begin_track("Dumping metadata");
    dumpMetadata(group, examples);
    LogInfo.end_track();
    LogInfo.begin_track("Examples");

    for (int e = 0; e < examples.size(); e++) {
      Example ex = examples.get(e);
      LogInfo.begin_track_printAll("%s: example %s/%s: %s", prefix, e, examples.size(), ex.id);
      ex.log();
      Execution.putOutput("example", e);
      StopWatchSet.begin("Parser.parse");
      ParserState state = builder.parser.parse(params, ex, false);
      StopWatchSet.end();
      out.printf("########## Example %s ##########\n", ex.id);
      dumpExample(exampleToLispTree(state));
      LogInfo.logs("Current: %s", ex.evaluation.summary());
      evaluation.add(ex.evaluation);
      LogInfo.logs("Cumulative(%s): %s", prefix, evaluation.summary());
      LogInfo.end_track();
      ex.predDerivations.clear(); // To save memory
    }

    LogInfo.end_track();
    LogInfo.logs("Stats for %s: %s", prefix, evaluation.summary());
    evaluation.logStats(prefix);
    evaluation.putOutput(prefix);
    LogInfo.end_track();
  }
Esempio n. 2
0
 private void updateConfusionMatrix(
     ConfusionMatrix m, Example ex, double compatDecisionThreshold, double probDecisionThreshold) {
   List<Derivation> derivations = ex.getPredDerivations();
   double[] probs = Derivation.getProbs(derivations, 1.0d);
   for (int i = 0; i < derivations.size(); i++) {
     Derivation deriv = derivations.get(i);
     double gold, pred;
     if (compatDecisionThreshold == -1.0d) gold = deriv.getCompatibility();
     else gold = (deriv.getCompatibility() > compatDecisionThreshold) ? 1.0d : 0.0d;
     if (probDecisionThreshold == -1.0d) pred = probs[i];
     else pred = (probs[i] > probDecisionThreshold) ? 1.0d : 0.0d;
     m.tp += gold * pred;
     m.fn += gold * (1.0d - pred);
     m.fp += (1.0d - gold) * pred;
     m.tn += (1.0d - gold) * (1.0d - pred);
   }
 }