def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
python类config_megam()的实例源码
rte_classify.py 文件源码
项目：PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
项目源码
文件源码
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def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
def demo():
import nltk
try:
nltk.config_megam('/usr/local/bin/megam')
trainer = lambda x: nltk.MaxentClassifier.train(x, 'megam')
except ValueError:
try:
trainer = lambda x: nltk.MaxentClassifier.train(x, 'BFGS')
except ValueError:
trainer = nltk.MaxentClassifier.train
nltk.classify.rte_classifier(trainer)
