content = '%s,%s\n' % (eachLine, clfResults[resultCounter])
fw.write(content)
resultCounter += 1
if __name__ == "__main__":
reload(sys)
sys.setdefaultencoding('utf8')
initDirectories()
handleArgv()
if Config.PRE_PROCESS_ON == 1:
xmlConverter = XmlConverter()
xmlConverter.convertDoc(0, Config.DATA_SIZE)
xmlConverter.convertQuery(0, Config.QUERY_SIZE)
xmlConverter.convertTestData(0, Config.TEST_DATA_SIZE)
else:
docReader = DocReader()
docModeler = DocModeler()
trainDataReader = TrainDataReader()
featureModeler = FeatureBasedModeler()
Y, trainDataIdxs = trainDataReader.getTrainAnswers()
print "Get Train Answers Done"
tfidfMat, Y = featureModeler.extractFeaturesMatrix(trainDataIdxs, Y)
print "Calc data features done"
'''
print tfidfMat.shape
transformer = random_projection.SparseRandomProjection(n_components=700000)