urllib.error.URLError: urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl.c:777) 解决办法

from sklearn.naive_bayes import MultinomialNB
from sklearn.datasets import fetch_20newsgroups
def article_category():
    categories = ['alt.atheism','soc.religion.christian','comp.graphics','sci.med']
    twenty_train = fetch_20newsgroups(subset='train',categories=categories)
    tfidf_transformer = TfidfVectorizer()
    X_train_tfidf = tfidf_transformer.fit_transform(twenty_train.data)
    clf = MultinomialNB(alpha=1.0).fit(X_train_tfidf, twenty_train.target)
    docs_new = ['Chemical reaction', ' Intel CPU is good']
    X_new_tfidf = tfidf_transformer.transform(docs_new)
    predicted = clf.predict(X_new_tfidf)
    for doc, category in zip(docs_new,predicted):
        print('%r => %s' % (doc, twenty_train.target_names[category]))

article_category()

在运行上述代码时候，报了一个错误

urllib.error.URLError: <urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed 

解决办法：

from sklearn.naive_bayes import MultinomialNB
from sklearn.datasets import fetch_20newsgroups
import ssl
ssl._create_default_https_context = ssl._create_unverified_context

def article_category():
    categories = ['alt.atheism','soc.religion.christian','comp.graphics','sci.med']
    twenty_train = fetch_20newsgroups(subset='train',categories=categories)
    tfidf_transformer = TfidfVectorizer()
    X_train_tfidf = tfidf_transformer.fit_transform(twenty_train.data)
    clf = MultinomialNB(alpha=1.0).fit(X_train_tfidf, twenty_train.target)
    docs_new = ['Chemical reaction', ' Intel CPU is good']
    X_new_tfidf = tfidf_transformer.transform(docs_new)
    predicted = clf.predict(X_new_tfidf)
    for doc, category in zip(docs_new,predicted):
        print('%r => %s' % (doc, twenty_train.target_names[category]))

article_category()

这样就可以解决了，如果你想想完美输出上面代码结果还需要下载一个东西，如果你的电脑自动下载那估计没问题，如果手动下载把文件放入用户目录下面的