print '\nTraining Classifiers:\n'
# forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls = clf.train_classifiers(tweets_features,train_labels)
forest_cls, svm_cls, lr_cls, ada_cls = clf.train_classifiers(
tweets_features, train_labels)
'''
Create results dataset from classifiers. Where each attribute is a classifier and each row corresponds to the
classification of a tweet according to each classifier.
'''
print '\nCreating Train set for super classifier ... '
test_tweet_trans = vectorizer.transform(test_tweets)
test_tweet_trans = test_tweet_trans.toarray()
# classifiers = (forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls)
classifiers = (forest_cls, svm_cls, lr_cls, ada_cls)
train_results = clf.test_classifiers(test_tweet_trans, test_labels,
classifiers)
'''
Train the super classifier on the test set
'''
xmlTestFile = '../DATA/general-tweets-test1k.xml'
tweets = xml.readXMLTest(xmlTestFile)
tokenized_tweets = []
tweetids = []
for tweet in tweets:
tokenized_tweets.append(ut.tokenize(tweet.content, tweet.polarity))
tweetids.append(tweet.id)
tweets = []
labels = []
'''
print '\nTraining Classifiers:\n'
# forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls = clf.train_classifiers(tweets_features,train_labels)
forest_cls, svm_cls, lr_cls, ada_cls = clf.train_classifiers(tweets_features, train_labels)
'''
Create results dataset from classifiers. Where each attribute is a classifier and each row corresponds to the
classification of a tweet according to each classifier.
'''
print '\nCreating Train set for super classifier ... '
test_tweet_trans = vectorizer.transform(test_tweets)
test_tweet_trans = test_tweet_trans.toarray()
# classifiers = (forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls)
classifiers = (forest_cls, svm_cls, lr_cls, ada_cls)
train_results = clf.test_classifiers(test_tweet_trans, test_labels, classifiers)
'''
Train the super classifier on the test set
'''
print '\nCreating Test set for super classifier ... '
val_tweet_trans = vectorizer.transform(validation_tweets)
val_tweet_trans = val_tweet_trans.toarray()
test_results = clf.test_classifiers(val_tweet_trans, validation_labels, classifiers)
'''
Now we have a train_results and test_results. Lets train and test a super classifier
'''
print '\nTraining super classifier ... '
super_clf = clf.rbf_classifier(train_results, test_labels)
print '\nTraining Classifiers:\n'
# forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls = clf.train_classifiers(tweets_features,train_labels)
forest_cls, svm_cls, lr_cls, ada_cls = clf.train_classifiers(
tweets_features, train_labels)
'''
Create results dataset from classifiers. Where each attribute is a classifier and each row corresponds to the
classification of a tweet according to each classifier.
'''
print '\nCreating Train set for super classifier ... '
test_tweet_trans = vectorizer.transform(test_tweets)
test_tweet_trans = test_tweet_trans.toarray()
# classifiers = (forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls)
classifiers = (forest_cls, svm_cls, lr_cls, ada_cls)
train_results = clf.test_classifiers(test_tweet_trans, test_labels,
classifiers)
'''
Train the super classifier on the test set
'''
print '\nCreating Test set for super classifier ... '
val_tweet_trans = vectorizer.transform(validation_tweets)
val_tweet_trans = val_tweet_trans.toarray()
test_results = clf.test_classifiers(val_tweet_trans, validation_labels,
classifiers)
'''
Now we have a train_results and test_results. Lets train and test a super classifier
'''
print '\nTraining super classifier ... '
super_clf = clf.rbf_classifier(train_results, test_labels)
'''
print '\nTraining Classifiers:\n'
# forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls = clf.train_classifiers(tweets_features,train_labels)
forest_cls, svm_cls, lr_cls, ada_cls = clf.train_classifiers(tweets_features, train_labels)
'''
Create results dataset from classifiers. Where each attribute is a classifier and each row corresponds to the
classification of a tweet according to each classifier.
'''
print '\nCreating Train set for super classifier ... '
test_tweet_trans = vectorizer.transform(test_tweets)
test_tweet_trans = test_tweet_trans.toarray()
# classifiers = (forest_cls, svm_cls, rbf_cls, ada_cls, lr_cls)
classifiers = (forest_cls, svm_cls, lr_cls, ada_cls)
train_results = clf.test_classifiers(test_tweet_trans, test_labels, classifiers)
'''
Train the super classifier on the test set
'''
xmlTestFile = '../DATA/general-tweets-test1k.xml'
tweets = xml.readXMLTest(xmlTestFile)
tokenized_tweets = []
tweetids = []
for tweet in tweets:
tokenized_tweets.append(ut.tokenize(tweet.content, tweet.polarity))
tweetids.append(tweet.id)
tweets = []