项目实战之train_model模块之word2vec训练

AI壹号堂 2023-01-13 00:14:18
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AI实战-冠状病毒推文NLP文本分类数据 分析预测实例(含20个源代码+10.97 MB完整的数据集) 代码手工整理,无语法错误,可运行。 包括:20个代码,共188.95 KB;数据大小:2个文件共10.97 MB。 使用到的模块: pandas numpy matplotlib.pyplot seaborn sklearn.model_selection.train_test_split sklearn.model_selection.GridSearchCV sklearn.feature_extraction.text.TfidfVectorizer sklearn.svm.SVC sklearn.linear_model.LogisticRegression sklearn.ensemble.RandomForestClassifier sklearn.ensemble.GradientBoostingClassifier sklearn.naive_bayes.MultinomialNB sklearn.metrics.classification_report sklearn.metrics.accuracy_score sklearn.utils.shuffle tensorflow.keras.models.Sequential tensorflow.keras.layers.Embedding tensorflow.keras.layers.SimpleRNN tensorflow.keras.layers.LSTM tensorflow.keras.layers.Dense tensorflow.keras.layers.Dropout tensorflow.keras.preprocessing.text.Tokenizer tensorflow.keras.preprocessing.sequence.pad_sequences nltk xgboost wordcloud.WordCloud keras_tuner tensorflow.keras.optimizers.Adam tensorflow.keras.callbacks.EarlyStopping nltk.corpus.stopwords tensorflow re string tensorflow.keras.models.Model tensorflow.keras.layers.GlobalMaxPooling1D tensorflow.keras.layers.(Dense tensorflow.keras.metrics.Accuracy sklearn.preprocessing.LabelEncoder keras.callbacks.EarlyStopping os nltk.stem.wordnet.WordNetLemmatizer nltk.stem.porter.PorterStemmer nltk.corpus.wordnet nltk.stem.WordNetLemmatizer tqdm.tqdm gensim sklearn.metrics.confusion_matrix tensorflow.keras.layers.Input tensorflow.keras joblib warnings nltk.tokenize.word_tokenize keras.utils.to_categorical gensim.models.Word2Vec tensorflow.keras.layers.Bidirectional tensorflow.keras.regularizers.l2 tensorflow.keras.models.load_model sklearn.preprocessing transformers.DistilBertTokenizerFast transformers.TFDistilBertForSequenceClassification transformers.create_optimizer keras.callbacks.ReduceLROnPlateau nltk.stem.PorterStemmer tensorflow.keras.Sequential textblob.TextBlob sklearn.feature_extraction.text.CountVectorizer sklearn.naive_bayes.ComplementNB sklearn.naive_bayes.GaussianNB sklearn.neural_network
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