# emotion_classification_based_on_machine_learning
基于机器学习的情绪分类
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##简介
       四种基于机器学习的情绪分类方法，分别为支持向量机（SVM）、朴素贝叶斯联合支持向量机（Naive Bayesian+SVM）、朴素贝叶斯联合K最近邻（Naive Bayesian+KNN）、朴素贝叶斯联合多标签K近邻（Naive Bayesian+MLKNN）。
基于机器学习的情绪分类+源代码+文档说明
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2023-11-09
16:05:40
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emotion_classification_based_on_machine_learning-master.zip （75个子文件） 
emotion_classification_based_on_machine_learning-master 
.gitattributes 378B NB+MLKNN performance.pyc 8KB weibo_e 3.06MB mlKNN.py 11KB performance.py 11KB
result_old.txt 63KB dic_intention_polarity.txt 482KB kafang3000 59KB result_emotion_bo.txt 20KB train_emotion_label.txt 15KB test.py 4KB label.txt 128KB test.out 62KB smile_new_new.txt 8KB train_emotion_e 652KB .gitignore 649B README.md 400B NB+SVM train.xml 2.04MB extract.py 2KB train_emotion.txt 535KB quzao.py 3KB train_none_emotion_quzao.txt 489KB fenci + featureSet+NB weibo_train_emotion.txt_fenci 668KB performance.pyc 7KB train_quzao_e 1.23MB test_nb 214KB kafang1 487KB train_libsvm 55KB test_libsvm 174KB performance.py 11KB train_none_emotion_e.txt 602KB nb0.out 29KB dic_intention_polarity.txt 482KB train_emotion_e.txt 650KB test.out5 60KB process1_final.py 14KB result_emotion_mu.txt 20KB test_quzao_e.txt 3.06MB NB_SVM_RESULT1 12KB train_nb 99KB result_emotion_bo.txt 20KB train_emotion_label.txt 15KB label.txt 128KB nb_pro 50KB emotion.py 1020B weibo_test.txt_fenci 3.13MB train_label_int.txt 8KB websites.txt 11KB train_emotion_quzao.txt 523KB train_none_emotion.txt 498KB train_emotion_label.txt 15KB SVM(word+punctuation+DUTIR) libsvm.py 3KB weibo_label.txt 128KB performance.pyc 7KB performance.py 11KB test_libsvm_all 2.58MB train_libsvm_all 1.11MB process.py 3KB test_quzao.txt_fenci 3.06MB svm.out 20KB train_quzao.txt_fenci 1.23MB dic_DUTIR.txt 507KB train_label_int.txt 8KB NB+KNN performance.pyc 7KB weibo_e 3.06MB performance.py 11KB result_old.txt 62KB dic_intention_polarity.txt 482KB KNN.py 8KB kafang3000 59KB result_emotion_bo.txt 20KB train_emotion_label.txt 15KB label.txt 128KB smile_new_new.txt 8KB train_emotion_e 652KB资源评论
