def evaluate(self, knowledge):
"""
If a gold standard was given, compute precision and recall for current
knowledge.
"""
if self.gold_standard:
logger.debug(u'running evaluate')
result = evaluate(knowledge, self.gold_standard)
logger.info(u'Precision: {}'.format(result['precision']))
logger.info(u'Recall: {}'.format(result['recall']))
return knowledge
"""
IEPY's result evaluator w.r.t. a reference corpus.
Usage:
eval.py <dbname> <proposed_csv> <reference_csv>
eval.py -h | --help | --version
Options:
-h --help Show this screen
--version Version number
"""
from docopt import docopt
from iepy.db import connect
from iepy.utils import load_evidence_from_csv, evaluate
if __name__ == '__main__':
opts = docopt(__doc__, version=0.1)
connector = connect(opts['<dbname>'])
proposed_csv = opts['<proposed_csv>']
reference_csv = opts['<reference_csv>']
proposed = load_evidence_from_csv(proposed_csv, connector)
reference = load_evidence_from_csv(reference_csv, connector)
result = evaluate(proposed, reference)
print("Precision: %.2f" % result['precision'])
print("Recall: %.2f" % result['recall'])