怎么使用TextBlob进行交叉验证

导入必要的库和数据集：

from textblob import TextBlobfrom sklearn.model_selection import cross_val_scorefrom sklearn.feature_extraction.text import CountVectorizerfrom sklearn.naive_bayes import MultinomialNBfrom sklearn.pipeline import make_pipelinefrom sklearn.datasets import fetch_20newsgroups

加载数据集：

categories = ['alt.atheism', 'comp.graphics', 'sci.med', 'soc.religion.christian']data = fetch_20newsgroups(categories=categories)X = data.datay = data.target

创建pipeline，包括文本向量化和分类模型：

model = make_pipeline(CountVectorizer(), MultinomialNB())

使用cross_val_score进行交叉验证：

scores = cross_val_score(model, X, y, cv=5, scoring='accuracy')print("Cross-validation scores: ", scores)print("Average score: ", scores.mean())

这样，你就可以使用TextBlob进行交叉验证了。