I was thinking if F1 score is usually correlated with support in classification problems. In theory, shouldn't the F1 score increase for a label if there is more support? Why does this not always happen?
Asked
Active
Viewed 351 times
0
-
2Possible duplicate of what does the numbers in the classification report of sklearn mean? – xiawi Jul 02 '19 at 07:08
-
I do know what each of these mean...what I would like to know if it is common that support effects f1 score and whether there is a direct correlation – Maria Jul 02 '19 at 07:13
-
1Having never heard the nomenclature "F1 score", for a moment I thought the question concerned the relationship between fan support of F1 teams (as in Formula 1) and their results at the end of the championship – Easymode44 Jul 02 '19 at 07:34
-
The support is the number of times each class appears in your data... Why would that necessarily correlate positively with a measure of performance of your model? – Frans Rodenburg Jul 10 '19 at 09:05
1 Answers
0
The support only relates to the ground truth. It is the same whathever your result is. On the contrary, the F1-score is computed from your actual scores thus depends from your results.
Thus, there is no direct link between support and F1-score in theory.
You can have an indirect link if the model performs better on a particular class. In that case, the more sample in that class, the larger the support and the higher the F1-score. But it is really due to the fact that
the model performs well on that class thus the F1-score increases
the class is larger thus the support is larger
xiawi
- 128
- 6