怎么使用TextBlob進(jìn)行交叉驗(yàn)證

小億
83
2024-05-13 12:17:15
欄目: 編程語言

  1. 導(dǎo)入必要的庫和數(shù)據(jù)集：
from textblob import TextBlob
from sklearn.model_selection import cross_val_score
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import make_pipeline
from sklearn.datasets import fetch_20newsgroups
  1. 加載數(shù)據(jù)集：
categories = ['alt.atheism', 'comp.graphics', 'sci.med', 'soc.religion.christian']
data = fetch_20newsgroups(categories=categories)
X = data.data
y = data.target
  1. 創(chuàng)建pipeline，包括文本向量化和分類模型：
model = make_pipeline(CountVectorizer(), MultinomialNB())
  1. 使用cross_val_score進(jìn)行交叉驗(yàn)證：
scores = cross_val_score(model, X, y, cv=5, scoring='accuracy')
print("Cross-validation scores: ", scores)
print("Average score: ", scores.mean())

這樣，你就可以使用TextBlob進(jìn)行交叉驗(yàn)證了。

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