Home/ Questions/Q 8974235
In Process

The Archive Base Latest Questions

Editorial Team
  • 0
Asked: 2026-06-15T18:38:07+00:00

I am really confused about how to calculate Precision and Recall in Supervised machine

  • 0

I am really confused about how to calculate Precision and Recall in Supervised machine learning algorithm using NB classifier

Say for example
1) I have two classes A,B
2) I have 10000 Documents out of which 2000 goes to training Sample set (class A=1000,class B=1000)
3) Now on basis of above training sample set classify rest 8000 documents using NB classifier
4) Now after classifying 5000 documents goes to class A and 3000 documents goes to class B
5) Now how to calculate Precision and Recall?

Please help me..

Thanks

Share

Leave an answer

You must login to add an answer.

Need An Account,

1 Answer

  1. Editorial Team

    Hi you have to divide results into four groups –
    True class A (TA) – correctly classified into class A
    False class A (FA) – incorrectly classified into class A
    True class B (TB) – correctly classified into class B
    False class B (FB) – incorrectly classified into class B

    precision = TA / (TA + FA)
    recall = TA / (TA + FB)

    You might also need accuracy and F-measure:

    accuracy = (TA + TB) / (TA + TB + FA + FB)
    f-measure = 2 * ((precision * recall)/(precision + recall))

    More here:
    http://en.wikipedia.org/wiki/Precision_and_recall#Definition_.28classification_context.29

    • 0