def train():
print "def train():"
textClassifier.context = prepareContext()
probabilities.context = textClassifier.splitContext()
x = OrderedDict(sorted(probabilities.classify("A pile on the earth strong for the burning".split()).iteritems(),key=operator.itemgetter(1),reverse=True))
print "probabilities.maxLikelyHood(x) = ",probabilities.maxLikelyHood(x)
print x
def train():
print "def train():"
textClassifier.context = prepareContext()
probabilities.context = textClassifier.splitContext()
x = OrderedDict(
sorted(probabilities.classify(
"A pile on the earth strong for the burning".split()).iteritems(),
key=operator.itemgetter(1),
reverse=True))
print "probabilities.maxLikelyHood(x) = ", probabilities.maxLikelyHood(x)
print x
probabilities.context = textClassifier.splitContext()
x = OrderedDict(
sorted(probabilities.classify(
"A pile on the earth strong for the burning".split()).iteritems(),
key=operator.itemgetter(1),
reverse=True))
print "probabilities.maxLikelyHood(x) = ", probabilities.maxLikelyHood(x)
print x
if __name__ == '__main__':
for i in TO_RUN:
if i and basic:
runBasics()
if i and train:
train()
if i and info:
print "prepare "
textClassifier.raw_context = prepareContext()
print "splitting "
textClassifier.raw_context = textClassifier.splitContext()
probabilities.context = textClassifier.raw_context
print "generating probabilities "
prepareProbabilisticContext()
print "dumping "
textClassifier.contextInfo()
# print textClassifier.context
print "Text Classify test "
print "The register of his burial was signed by the clergyman, the clerk, the undertaker"
# print "",textClassifier.classify("goose")
textClassifier.context = prepareContext()
probabilities.context = textClassifier.splitContext()
x = OrderedDict(sorted(probabilities.classify("A pile on the earth strong for the burning".split()).iteritems(),key=operator.itemgetter(1),reverse=True))
print "probabilities.maxLikelyHood(x) = ",probabilities.maxLikelyHood(x)
print x
if __name__ == '__main__':
for i in TO_RUN:
if i and basic:
runBasics()
if i and train:
train()
if i and info:
print "prepare "
textClassifier.raw_context = prepareContext()
print "splitting "
textClassifier.raw_context = textClassifier.splitContext()
probabilities.context = textClassifier.raw_context
print "generating probabilities "
prepareProbabilisticContext()
print "dumping "
textClassifier.contextInfo()
# print textClassifier.context
print "Text Classify test "
print "The register of his burial was signed by the clergyman, the clerk, the undertaker"
# print "",textClassifier.classify("goose")