print("Building features...")
feature_mapper = idf.IDFeatures(train, mode=mode)
#feature_mapper = exfc2.ExtendedFeatures(train,mode=mode)
feature_mapper.build_features()
#pdb.set_trace()
print("Init Struc Perceptron")
epochs = 5
learning_rate = 1
reg = 0 # extended feat
#reg = 0.001
sp = spc.StructuredPerceptron(train.x_dict,
train.y_dict,
feature_mapper,
num_epochs=epochs,
learning_rate=learning_rate,
reg_param=reg)
print("Training...")
sp.train_supervised_bigram(train)
print("Predicting...")
print("::Training...")
pred_train = sp.viterbi_decode_corpus_bigram(train)
print("::Valalidation...")
pred_val = sp.viterbi_decode_corpus_bigram(val)
print("::Testing...")
pred_test = sp.viterbi_decode_corpus_bigram(test)
print("Evaluating...")
eval_train = sp.evaluate_corpus(train, pred_train)
pred_dev = crf_online.viterbi_decode_corpus(dev_seq) pred_test = crf_online.viterbi_decode_corpus(test_seq) eval_train = crf_online.evaluate_corpus(train_seq, pred_train) eval_dev = crf_online.evaluate_corpus(dev_seq, pred_dev) eval_test = crf_online.evaluate_corpus(test_seq, pred_test) print "CRF - Extended Features Accuracy Train: %.3f Dev: %.3f Test: %.3f"%(eval_train, eval_dev,eval_test) print "Perceptron Exercise" feature_mapper = idfc.IDFeatures(train_seq) feature_mapper.build_features() sp = spc.StructuredPerceptron(corpus.word_dict, corpus.tag_dict, feature_mapper) sp.num_epochs = 20 sp.train_supervised(train_seq) pred_train = sp.viterbi_decode_corpus(train_seq) pred_dev = sp.viterbi_decode_corpus(dev_seq) pred_test = sp.viterbi_decode_corpus(test_seq) eval_train = sp.evaluate_corpus(train_seq, pred_train) eval_dev = sp.evaluate_corpus(dev_seq, pred_dev) eval_test = sp.evaluate_corpus(test_seq, pred_test) print "Structured Perceptron - ID Features Accuracy Train: %.3f Dev: %.3f Test: %.3f"%(eval_train,eval_dev,eval_test) feature_mapper = exfc.ExtendedFeatures(train_seq) feature_mapper.build_features()