def train(self, trainingSet):
for i in range(self.numIterations):
corpus = Parser.load_corpus(trainingSet)
oracle = Oracle()
for sentence in corpus:
self.initialize(sentence)
self.trackTypes(sentence)
while len(self.buff) > 0 or len(self.stack) > 1:
transition = oracle.getTransition(self.stack, self.buff,
self.dependentIDs,
self.arcs, self.labeled)
self.model.learn(transition, self.stack, self.buff,
self.labels, self.transitions, self.arcs,
self.wordsThatHaveHeads)
self.execute_transition(transition)
def train(self, trainingSet, model):
corpus = Parser.load_corpus(trainingSet)
oracle = Oracle()
for sentence in corpus:
self.initialize(sentence)
while len(self.buff) > 0 or len(self.stack) > 1:
transition = oracle.getTransition(self.stack, self.buff, \
self.leftmostChildren, self.rightmostChildren, \
self.arcs, self.labeled)
#model.learn(transition, self.stack, self.buff, \
# self.labels, self.transitions, self.arcs, sentence)
model.compile_svm_feats(transition, self.stack, self.buff, \
self.labels, self.transitions, self.arcs, sentence)
self.execute_transition(transition)
model.train_svm()
def train(self, trainingSet, model):
corpus = Parser.load_corpus(trainingSet)
oracle = Oracle()
for sentence in corpus:
self.initialize(sentence)
while len(self.buff) > 0 or len(self.stack) > 1:
transition = oracle.getTransition(self.stack, self.buff, \
self.leftmostChildren, self.rightmostChildren, \
self.arcs, self.labeled)
#model.learn(transition, self.stack, self.buff, \
# self.labels, self.transitions, self.arcs, sentence)
model.compile_svm_feats(transition, self.stack, self.buff, \
self.labels, self.transitions, self.arcs, sentence)
self.execute_transition(transition)
model.train_svm()
def train(self, trainingSet, model): corpus = Parser.load_corpus(trainingSet) oracle = Oracle() i = 0 for sentence in corpus: if i % 25 == 0: print >>sys.stderr, "%d/1921" % i i += 1 self.initialize(sentence) while len(self.buff) > 0 or len(self.stack) > 1: transition = oracle.getTransition(self.stack, self.buff, \ self.leftmostChildren, self.rightmostChildren, \ self.arcs, self.labeled) model.learn(transition, self.stack, self.buff, \ self.arcs, self.labels, self.transitions) self.execute_transition(transition) model.build_model()
def train(self, trainingSet):
for i in range(self.numIterations):
corpus = Parser.load_corpus(trainingSet)
oracle = Oracle()
for sentence in corpus:
self.initialize(sentence)
self.trackTypes(sentence)
while len(self.buff) > 0 or len(self.stack) > 1:
transition = oracle.getTransition(self.stack, self.buff, self.dependentIDs, self.arcs, self.labeled)
self.model.learn(
transition,
self.stack,
self.buff,
self.labels,
self.transitions,
self.arcs,
self.wordsThatHaveHeads,
)
self.execute_transition(transition)
