本文整理汇总了Python中Kernel.Utils.get_sentences方法的典型用法代码示例。如果您正苦于以下问题：Python Utils.get_sentences方法的具体用法？Python Utils.get_sentences怎么用？Python Utils.get_sentences使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Kernel.Utils的用法示例。
在下文中一共展示了Utils.get_sentences方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: Word2Vec
# 需要导入模块: from Kernel import Utils [as 别名]
# 或者: from Kernel.Utils import get_sentences [as 别名]
from Kernel import Config
from Kernel import Preprocess
from Kernel import Classifier
from Kernel import FeatureExtractor
from Kernel import Optimizer
from Kernel import Statistics
from Kernel import Utils
from gensim.models import Word2Vec
import logging
CORPUS = "./corpus_polaridad/"
if Config.VERBOSE: logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
## SAVE MODEL ##
sentences = Utils.get_sentences(CORPUS)
sentences = Preprocess.normalize_sentences(sentences,True,False,False,False,False,True,1)
model = Word2Vec([sentence for (sentence,cat) in sentences],min_count=Config.MIN_COUNT_W2V,size=Config.SIZE_W2V,window=Config.WINDOW_W2V)
sentences = FeatureExtractor.get_sentences_representation(sentences,model,Config.SENTENCE_REPRESENTATION)
Utils.serialize("dest.m",model)
Utils.serialize("sentences.m",sentences)
################
## STATISTICS ##
#sentences = Utils.get_sentences(CORPUS)
#sentences = Preprocess.normalize_sentences(sentences,True,False,False,False,False,True,1)
#Statistics.leaving_one_out_nearest(sentences,1)
#Statistics.leaving_one_out_supervised_classifier(sentences,Config.CLASSIFIER)
################
## TESTING PROJECT CLASSIFIER ##