def main(ftrain, fdev=None, fmodel='model/model.pickle.gz'):
# Load data
print 'Loading training data ...'
data = load(gzip.open(ftrain))
M, labels = data['data'], data['labels']
# Load dev data
if fdev is not None:
print 'Loading dev data ...'
devdata = load(gzip.open(fdev))
devM, devlabels = devdata['data'], devdata['labels']
else:
devM, devlabels = None, None
# Training with specified parameters
print 'Training ...'
clf = Classifier()
clf.train(M, labels, devM, devlabels)
clf.savemodel(fmodel)
def main(ftrain, fdev=None, fmodel='model/model.pickle.gz'):
# Load data
print 'Loading training data ...'
data = load(gzip.open(ftrain))
M, labels = data['data'], data['labels']
# Load dev data
if fdev is not None:
print 'Loading dev data ...'
devdata = load(gzip.open(fdev))
devM, devlabels = devdata['data'], devdata['labels']
else:
devM, devlabels = None, None
# Training with specified parameters
print 'Training ...'
clf = Classifier()
clf.train(M, labels, devM, devlabels)
clf.savemodel(fmodel)
