Answers.Body: <p>I could get perfect sensitivity for positive sentiment if I always predict positive sentiment, but my accuracy could be 50%ish depending on the distribution of positive sentiment in the data. The sensitivity and accuracy scores alone are not enough to tell you if your model is any good, you will need to have some goal that you are trying to achieve e.g., get 70% accuracy.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-12-08T04:12:53.607Z
Answers.Text: Additionally to what Cameron said, check for bias in your dataset, if your dataset is 65% positive... I think you can probably see why that would be an issue
Answers.UserDisplayName: Recessive
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-06-09T12:05:43.473Z
Answers.LastActivityDate: 2021-06-09T12:05:43.473Z
Answers.UserDisplayName: Cameron Chandler
Body: <p>I am creating a sentiment analysis model using Naive Bayes. When I test the model, I get an average accuracy of 65%; however, the sensitivity of the model is much higher, 90%.</p>
  <p>So, I am wondering if there are methods to fixing this data; or, since the sensitivity is very high, then would it be ok to move forward with the model?</p>
  
Tags: <accuracy><sentiment-analysis><naive-bayes><sensitivity>
Title: Is it ok to have an accuracy of 65% and a sensitivity of 90% with Naive Bayes for sentiment analysis?
UserDisplayName: Sebastian
ThreadText: # Is it ok to have an accuracy of 65% and a sensitivity of 90% with Naive Bayes for sentiment analysis?
  
  (Asked by: username_0 on 2021-06-08)
  
  I am creating a sentiment analysis model using Naive Bayes. When I test the model, I get an average accuracy of 65%; however, the sensitivity of the model is much higher, 90%.
  
  So, I am wondering if there are methods to fixing this data; or, since the sensitivity is very high, then would it be ok to move forward with the model?
  
  **Tags:** accuracy, sentiment-analysis, naive-bayes, sensitivity
  
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  ## 1 answers
  
  ### Answer by username_1 on 2021-06-09. Score: 1
  
  I could get perfect sensitivity for positive sentiment if I always predict positive sentiment, but my accuracy could be 50%ish depending on the distribution of positive sentiment in the data. The sensitivity and accuracy scores alone are not enough to tell you if your model is any good, you will need to have some goal that you are trying to achieve e.g., get 70% accuracy.
  
  > **Comments:**
  > **username_2**: Additionally to what Cameron said, check for bias in your dataset, if your dataset is 65% positive... I think you can probably see why that would be an issue  
  
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