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TCM_entity_recognition
TCM_entity_recognition Public中医药术语识别,使用CNN-BILSTM-CRF模型对9000条训练数据和1000条测试数据进行处理,最终测试数据正确率为90+%。为方便使用,使用Tkinter对模型进行封装使用
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MI_Naive_Bayesian
MI_Naive_Bayesian Public基于互信息熵的朴素贝叶斯分类,数据集选择英文的恶意邮件,首先通过tf-idf对文本特征化,后通过高斯分布对连续特征概率进行估计,使用互信息进行加权,最终正确率为94%,想对比原始朴素贝叶斯分类提高4%左右
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