def loading_ftr_CRFs(command):
##############################################################################
if command == 'twitter_vs_sgforums_twitter_training':
# loading CRF features for training
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF/crf_features/features_rmLink'
elif command == 'twitter_vs_sgforums_sgforums_testing':
# loading CRF features for testing
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/CRFs_compareModel/sgforums/ftr_twitter'
##############################################################################
if command == 'twitter_vs_facebook_twitter_training':
# loading CRF features for training
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF/crf_features/features_rmLink'
elif command == 'twitter_vs_facebook_facebook_testing':
# loading CRF features for testing
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/CRFs_compareModel/facebook/ftr_twitter'
##############################################################################
elif command == 'sgforums_vs_twitter_sgforums_training':
# features for training
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/sgforums/20152207_singaporebuses_all_posts/labeling_CRF/crf_features/features'
elif command == 'sgforums_vs_twitter_twitter_testing':
# features for testing
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/CRFs_compareModel/twitter/ftr_sgforums'
##############################################################################
elif command == 'sgforums_vs_facebook_sgforums_training':
# features for training
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/sgforums/20152207_singaporebuses_all_posts/labeling_CRF/crf_features/features'
elif command == 'sgforums_vs_facebook_facebook_testing':
# features for testing
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/CRFs_compareModel/facebook/ftr_sgforums'
##############################################################################
elif command == 'facebook_vs_twitter_facebook_training':
# features for training
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/facebook/BusNews/labeling_CRF/crf_features/features'
elif command == 'facebook_vs_twitter_twitter_testing':
# features for testing
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/CRFs_compareModel/twitter/ftr_facebook'
##############################################################################
elif command == 'facebook_vs_sgforums_facebook_training':
# features for training
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/facebook/BusNews/labeling_CRF/crf_features/features'
elif command == 'facebook_vs_sgforums_sgforums_testing':
# features for testing
path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/CRFs_compareModel/sgforums/ftr_facebook'
files_ = folder_files(path_ftr)
features = featuers_CRF(files_, path_ftr)
X = np.array(construct_ftr_CRF(features)) # construct the features for CRF
print 'Finish loading features for CRF ' + command
return X
num_list_sentence = np.array(list_ftr_sentence) # IMPORTANT. We need to convert to array before adding to list
list_all_sentences.append(num_list_sentence)
return list_all_sentences
if __name__ == "__main__":
start = timeit.default_timer() # get the start time
# loading CRF features
# path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF/crf_features/features_rmLinkWordVector/wordVec_30'
# path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF/crf_features/features_rmLinkWordVector/wordVec_70'
# path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF/crf_features/features_rmLinkWordVector/wordVec_100'
# path_ftr = 'D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF/crf_features/features_rmLinkWordVector/wordVec_150'
path_ftr = "D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF/crf_features/features_rmLinkWordVector/wordVec_200"
files_ = folder_files(path_ftr)
features = featuers_CRF(files_, path_ftr)
# construct_ftr_CRF_wordVector(features)
X = np.array(construct_ftr_CRF_wordVector(features)) # construct the features for CRF
print X.shape
print "Finish loading features for CRF"
#
# # loading target labels
path_ = "D:/Project/Transportation_SMU-NEC_collaboration/Data/twitter/labeling_CRF"
name_ = "labeling_all.txt"
list_line_ = filterTxt_CRF(load_file(path_, name_), "removeLink", "model")
Y = np.array(load_target_label(list_line_))
print Y.shape
print "Finish loading target label"
#
# # for index in range(0, len(X)):
# # print len(X[index]), len(Y[index])
