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word2vec+cnn_shortAd_Classification

微信广告正负样本分类

参考https://github.com/clayandgithub/zh_cnn_text_classify.git

Dependencies

tensorflow (1.6 run success) 未做分词,直接单个词处理

正样本:

  • xx,xxx,xxxxxxxxx

负样本:

  • 微信公众号 AppSo,回复「钱包」看看微信钱包这 6 个秘密使用技巧

  • 微信号:wszs1981

  • 长按二维码关注

训练数据集:data/ad_5000.txt 、 data/not_ad_4000.txt

python train.py

测试数据集:data/ad_5000.txt ad_5000_label、data/not_ad_4000.txt not_ad_4000_label 、 data/test.txt test_label 查看运行结果:

python eval.py

result

#data/prediction_ad_5000.txt
Total number of test examples: 5000
Accuracy: 0.9944

#data/prediction_not_ad_4000.txt
Total number of test examples: 4000
Accuracy: 0.99475

#对于某些样本泛化能力不强 data/prediction_test.txt
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