如何计算精度和F1？

Question

我使用TF_IDF作为特征选择和朴素贝叶斯分类器。我想计算出总精度和精度。

accuracy = train_model(naive_bayes.MultinomialNB(), xtrain_count, train_y, xvalid_count)
  print("NB, Count Vectors: ", accuracy)

 # Naive Bayes on Word Level TF IDF Vectors
  accuracy = train_model(naive_bayes.MultinomialNB(), xtrain_tfidf, train_y, xvalid_tfidf)
    print("NB, WordLevel TF-IDF: ", accuracy)

    # Naive Bayes on Ngram Level TF IDF Vectors
   accuracy = train_model(naive_bayes.MultinomialNB(), xtrain_tfidf_ngram, train_y, 
   xvalid_tfidf_ngram)
  print("NB, N-Gram Vectors: ", accuracy)

 # Naive Bayes on Character Level TF IDF Vectors
  accuracy = train_model(naive_bayes.MultinomialNB(), xtrain_tfidf_ngram_chars, train_y, 
   xvalid_tfidf_ngram_chars)
  print("NB, CharLevel Vectors: ", accuracy)

Answer 1

用这个：

from sklearn.metrics import classification_report

print(classification_report(true_value,predicted_value))

这会给你你想要的一切