You can also activate the monitor from command line, using misclassified and detailedF:
bin/opennlp TokenNameFinderCrossValidator Usage: opennlp TokenNameFinderCrossValidator[.ontonotes|.bionlp2004|.conll03|.conll02|.ad|.evalita|.muc6|.brat] [-factory factoryName] [-resources resourcesDir] [-type modelType] [-featuregen featuregenFile] [-nameTypes types] [-sequenceCodec codec] [-params paramsFile] -lang language [-misclassified true|false] [-folds num] [-detailedF true|false] -data sampleData [-encoding charsetName] Arguments description: -factory factoryName A sub-class of TokenNameFinderFactory -resources resourcesDir The resources directory -type modelType The type of the token name finder model -featuregen featuregenFile The feature generator descriptor file -nameTypes types name types to use for training -sequenceCodec codec sequence codec used to code name spans -params paramsFile training parameters file. -lang language language which is being processed. -misclassified true|false if true will print false negatives and false positives. -folds num number of folds, default is 10. -detailedF true|false if true will print detailed FMeasure results. -data sampleData data to be used, usually a file name. -encoding charsetName encoding for reading and writing text, if absent the system default is used. William Colen 2016-06-28 11:04 GMT-03:00 William Colen <william.co...@gmail.com>: > > https://opennlp.apache.org/documentation/1.6.0/manual/opennlp.html#tools.namefind.training.featuregen > > Do you have a specific question? > > You can try the default feature generator and check how your model will > perform in terms of precision and recall. You can take a look at the kind > of errors (use a EvaluationMonitor > https://opennlp.apache.org/documentation/1.6.0/apidocs/opennlp-tools/opennlp/tools/util/eval/EvaluationMonitor.html) > and try to figure out features that it is missing that would give a hint > how to perform better. > Add the features and check precision and recall again. > > 2016-06-21 13:45 GMT-03:00 <rakeshbe...@gmail.com>: > >> Please share the usages of Adaptive features that are used in NER tagging? >> >> Regards, >> Rakesh.P >> > >