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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?

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    $\begingroup$ Possible duplicate of what does the numbers in the classification report of sklearn mean? $\endgroup$ – xiawi Jul 2 at 7:08
  • $\begingroup$ 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 $\endgroup$ – Maria Jul 2 at 7:13
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    $\begingroup$ Having 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 $\endgroup$ – Easymode44 Jul 2 at 7:34
  • $\begingroup$ 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? $\endgroup$ – Frans Rodenburg Jul 10 at 9:05
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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

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