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如果文本里有不是中文的请翻译成中文。"content = re.sub("[s .!/_,$%^*( "'] |[a-zA-Z0-9 ——,。!、:~@#¥%……&*()] ", "", content_raw)print(content_raw)print(content)``````pythonfrom sklearn.feature_extraction.text import CountVectorizercv = CountVectorizer(ngram_range=(2,2))# 构建字典cv_fit = cv.fit_transform([content])# 获取词袋print(cv.get_feature_names())``````python# 单独一个文件from sklearn.feature_extraction.text import CountVectorizercv = CountVectorizer()# 构建字典cv_fit = cv.fit_transform([content])# 获取词袋print(cv.get_feature_names())``````python# 单独一个文件from sklearn.feature_extraction.text import CountVectorizercv = CountVectorizer()# 构建字典cv_fit = cv.fit_transform([content])# 获取词袋print(cv.get_feature_names())print(cv_fit.toarray())``````pythonfrom sklearn.feature_extraction.text import TfidfVectorizertv = TfidfVectorizer()tv_fit = tv.fit_transform([content])print(tv.get_feature_names())print(tv_fit.toarray())``````pythonimport jieba# 分词content = jieba.cut(content)res = " ".join(content)print(res) ``````python# 分词content = jieba.cut(content)res = " ".join(content)print(res) from sklearn.feature_extraction.text import TfidfVectorizertv = TfidfVectorizer()tv_fit = tv.fit_transform([res])print(tv.get_feature_names())print(tv_fit.toarray())``````python# 分词content = jieba.cut(content)res = " ".join(content)print(res) from sklearn.feature_extraction.text import CountVectorizercv = CountVectorizer()cv_fit = cv.fit_transform([res])print(cv.get_feature_names())print(cv_fit.toarray())``````python# 分词content = jieba.cut(content)res = " ".join(content)print(res) # 构建字典from sklearn.feature_extraction.text import TfidfVectorizertv = TfidfVectorizer()tv_fit = tv.fit_transform([res])# 获取词袋print(tv.get_feature_names())print(tv_fit.toarray())``````python# 分词content = jieba.cut(content)res = " ".join(content)print(res) # 调用from sklearn.feature_extraction.text import HashingVectorizerhv = HashingVectorizer(n_features=6)hv_fit = hv.fit_transform([res])# 获取词袋print(hv.get_feature_names())print(hv_fit.toarray())```---如果遇到问题请发邮件至:naer7403@gmail.com 并标明 模块名称,谢谢。

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