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I know it sounds incorrect but that is the truth

Here let me show you

This below one is the first one and very widely used in the literature

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First one reference : Steinbach, Michael, George Karypis, and Vipin Kumar. "A comparison of document clustering techniques." KDD workshop on text mining. Vol. 400. No. 1. 2000.

And the second one is this one : http://nlp.stanford.edu/IR-book/html/htmledition/evaluation-of-clustering-1.html

Here an answer about second one : https://stats.stackexchange.com/a/80194/5263

The second one is pretty complex and hard to understand

I coded both and they produce different results

I believe second one is better evaluation but the question is

Why there are 2 different F1-Measure? Which one is better and why?

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  • $\begingroup$ At the end of your first page, it says $F_\beta = \frac{(1+\beta^2)PR}{\beta^2P + R}$, which, for $\beta = 1$, is the $F_1$ score. This is the $F_\beta$ score, a generalization (see Wikipedia). What did you mistake for the $F_1$ score in your link? $\endgroup$ – Winks Mar 30 '16 at 21:37
  • $\begingroup$ @Winks so you say F1-Score and F-Measure are different things? $\endgroup$ – MonsterMMORPG Mar 30 '16 at 21:48
  • $\begingroup$ @Winks because wikipedia tells F-Measure and F1-Score are same things $\endgroup$ – MonsterMMORPG Mar 30 '16 at 21:48
  • $\begingroup$ @Winks 1 more thing. How do you format your answer that way in comment section :D $\endgroup$ – MonsterMMORPG Mar 30 '16 at 21:51

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