我想使用邏輯回歸預(yù)測情感分析模型的準(zhǔn)確性，但出現(xiàn)錯誤：錯誤的輸入形狀（使用輸入進行編輯）數(shù)據(jù)框：dfsentence                | polarity_labelnew release!            | positivebuy                     | neutralleast good-looking      | negative代碼：from sklearn.preprocessing import OneHotEncoder                                                   from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer, ENGLISH_STOP_WORDS# Define the set of stop wordsmy_stop_words = ENGLISH_STOP_WORDSvect = CountVectorizer(max_features=5000,stop_words=my_stop_words)vect.fit(df.sentence)X = vect.transform(df.sentence)y = df.polarity_labelencoder = OneHotEncoder()encoder.fit_transform(y)from sklearn.linear_model import LogisticRegressionfrom sklearn.model_selection import train_test_splitX_train, X_test, y_train, y_test = train_test_split(X,y, test_size=0.2, random_state=123)LogisticRegression(penalty='l2',C=1.0)log_reg = LogisticRegression().fit(X_train, y_train)錯誤信息ValueError: Expected 2D array, got 1D array instead:array=['Neutral' 'Positive' 'Positive' ... 'Neutral' 'Neutral' 'Neutral'].Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.```How can I fix this?