public override void run(string format, string[] args)
{
base.run(format, args);
mlParams = CmdLineUtil.loadTrainingParameters(@params.Params, false);
if (mlParams == null)
{
mlParams = ModelUtil.createTrainingParameters(@params.Iterations.Value, @params.Cutoff.Value);
}
TokenizerCrossValidator validator;
TokenizerEvaluationMonitor listener = null;
if (@params.Misclassified.Value)
{
listener = new TokenEvaluationErrorListener();
}
try
{
Dictionary dict = TokenizerTrainerTool.loadDict(@params.AbbDict);
TokenizerFactory tokFactory = TokenizerFactory.create(@params.Factory, @params.Lang, dict, @params.AlphaNumOpt.Value, null);
validator = new TokenizerCrossValidator(mlParams, tokFactory, listener);
validator.evaluate(sampleStream, @params.Folds.Value);
}
catch (IOException e)
{
throw new TerminateToolException(-1, "IO error while reading training data or indexing data: " + e.Message, e);
}
finally
{
try
{
sampleStream.close();
}
catch (IOException)
{
// sorry that this can fail
}
}
FMeasure result = validator.FMeasure;
Console.WriteLine(result.ToString());
}
public override void run(string format, string[] args)
{
base.run(format, args);
TokenizerModel model = (new TokenizerModelLoader()).load(@params.Model);
TokenizerEvaluationMonitor misclassifiedListener = null;
if (@params.Misclassified.Value)
{
misclassifiedListener = new TokenEvaluationErrorListener();
}
TokenizerEvaluator evaluator = new TokenizerEvaluator(new opennlp.tools.tokenize.TokenizerME(model), misclassifiedListener);
Console.Write("Evaluating ... ");
try
{
evaluator.evaluate(sampleStream);
}
catch (IOException e)
{
Console.Error.WriteLine("failed");
throw new TerminateToolException(-1, "IO error while reading test data: " + e.Message, e);
}
finally
{
try
{
sampleStream.close();
}
catch (IOException)
{
// sorry that this can fail
}
}
Console.WriteLine("done");
Console.WriteLine();
Console.WriteLine(evaluator.FMeasure);
}
