true, false, null, 0, threads);
}
else if (MAXENT_QN_VALUE.equals(algorithmName)) {
int m = getIntParam(trainParams, "numOfUpdates", QNTrainer.DEFAULT_M, reportMap);
int maxFctEval = getIntParam(trainParams, "maxFctEval", QNTrainer.DEFAULT_MAX_FCT_EVAL, reportMap);
model = new QNTrainer(m, maxFctEval, true).trainModel(indexer);
}
else if (PERCEPTRON_VALUE.equals(algorithmName)) {
boolean useAverage = getBooleanParam(trainParams, "UseAverage", true, reportMap);
boolean useSkippedAveraging = getBooleanParam(trainParams, "UseSkippedAveraging", false, reportMap);