Skip to main content
Cross Validated

Return to Question

Became Hot Network Question
deleted 9 characters in body; edited tags
Source Link
kjetil b halvorsen ♦
kjetil b halvorsen ♦
  • 82.8k
  • 32
  • 201
  • 663

I am interested to understand in which scenarios person should use sensitivity, specificity, and when should person opt for precision recall.

On a high level I understand for a balanced data set we should use precision, recall and if dataset is imbalanced we should use sensitivity and specificity. but I am not sure why they say it. If you people have different perspective, pls throw some light on how to perceive these.

Thanks

I am interested to understand in which scenarios person should use sensitivity, specificity, and when should person opt for precision recall.

On a high level I understand for a balanced data set we should use precision, recall and if dataset is imbalanced we should use sensitivity and specificity. but I am not sure why they say it. If you people have different perspective, pls throw some light on how to perceive these.

Thanks

I am interested to understand in which scenarios person should use sensitivity, specificity, and when should person opt for precision recall.

On a high level I understand for a balanced data set we should use precision, recall and if dataset is imbalanced we should use sensitivity and specificity. but I am not sure why they say it. If you people have different perspective, pls throw some light on how to perceive these.

Source Link
Teja Bandaru
Teja Bandaru
  • 21
  • 2

Logistic regression metric

I am interested to understand in which scenarios person should use sensitivity, specificity, and when should person opt for precision recall.

On a high level I understand for a balanced data set we should use precision, recall and if dataset is imbalanced we should use sensitivity and specificity. but I am not sure why they say it. If you people have different perspective, pls throw some light on how to perceive these.

Thanks