def train(self, numIterations=100, testCorpusPath=None):
if testCorpusPath:
testCorpus = Corpus(testCorpusPath)
for i in range(1, numIterations + 1):
self.algorithm.train() # call train method from algorithm
if i % 10 == 0:
# trainEval = Evaluation(self.algorithm.corpus)
# print "Training evaluation for", i, "iteration(s):\n", trainEval.format()
# self.algorithm.corpus.resetSentStats()
if testCorpusPath:
self.setPredictedTags(testCorpus)
testEval = Evaluation(testCorpus)
print "Testing evaluation for", i, "iteration(s):\n",testEval.format()
testCorpus.resetSentStats() # !!! we can use prototype pattern(so we don't need to loop through sents): here testCorpus = testCorpus.getPrototype() and in Corpus::__init__ : self.prototype = self (google : python prototype)?
def train(self, numIterations=100, testCorpusPath=None):
if testCorpusPath:
testCorpus = Corpus(testCorpusPath)
for i in range(1, numIterations + 1):
self.algorithm.train() # call train method from algorithm
if i % 10 == 0:
# trainEval = Evaluation(self.algorithm.corpus)
# print "Training evaluation for", i, "iteration(s):\n", trainEval.format()
# self.algorithm.corpus.resetSentStats()
if testCorpusPath:
self.setPredictedTags(testCorpus)
testEval = Evaluation(testCorpus)
print "Testing evaluation for", i, "iteration(s):\n", testEval.format(
)
testCorpus.resetSentStats(
) # !!! we can use prototype pattern(so we don't need to loop through sents): here testCorpus = testCorpus.getPrototype() and in Corpus::__init__ : self.prototype = self (google : python prototype)?
