def process_batch(models, folder):
total = 0
no_correct = 0
confusion_matrix = dict()
paths = ioutils.list_files_only(folder)
for path in paths:
total += 1
with open(path, 'r') as f:
print 'Process file', path,
document = ngramprofile.build_profile(f)
document.language = os.path.splitext(os.path.basename(path))[0].split('-')[0]
predicted_language = identify_language(models, document)
print 'Predict:', predicted_language, 'expect:', document.language
if predicted_language == document.language:
no_correct += 1
else:
if document.language not in confusion_matrix:
confusion_matrix[document.language] = dict()
confusion_matrix[document.language][predicted_language] = confusion_matrix.get(predicted_language, 0) + 1
print 'Accuracy:', no_correct * 1.0 / total
def read_models(folder):
model_paths = ioutils.list_files_only(folder)
models = list()
for model_path in model_paths:
models.append(ngramprofile.load_profile(model_path))
return models
