fit_transform() 得到了意外的关键字参数 'dtype'

Question

from sklearn.feature_extraction.text import CountVectorizer
# Define the cleaning pipeline we defined earlier

vectorizer = CountVectorizer(analyzer = message_cleaning)
tweets_countvectorizer = vectorizer.fit_transform(tweets_df['tweet'], dtype = np.uint8)

TypeError Traceback（最后一次调用）在 3个 4 向量化器 = CountVectorizer(分析器 = message_cleaning) ----> 5 tweets_countvectorizer = vectorizer.fit_transform(tweets_df['tweet'], dtype = np.uint8)

TypeError: fit_transform() 得到了意外的关键字参数 'dtype'

Answer 1

应该将 dtype 参数传递给 CountVectorizer 的构造函数：

from sklearn.feature_extraction.text import CountVectorizer
# Define the cleaning pipeline we defined earlier

vectorizer = CountVectorizer(analyzer = message_cleaning, dtype = np.uint8)
tweets_countvectorizer = vectorizer.fit_transform(tweets_df['tweet'])

Answer 2

您需要在创建向量对象时将dtype参数传递给构造函数：

from sklearn.feature_extraction.text import CountVectorizer
# Define the cleaning pipeline we defined earlier

vectorizer = CountVectorizer(analyzer = message_cleaning, dtype = np.uint8)
tweets_countvectorizer = vectorizer.fit_transform(tweets_df['tweet'])

fit_transform() 得到了意外的关键字参数 'dtype'

fit_transform() got an unexpected keyword argument 'dtype'

python

arguments