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A value of MCC = 0 would be expected for a random prediction scheme.
As expected, the lack of correlation prevented the prediction of BLC36's corresponding to 5BLC's of 1994, giving <δ_pred> = 1.56 (close to the error for a random prediction).
The average sensitivity among all analyzed complexes was 57.7%, worse than CPORT but much better than the average sensitivity of 40.7% for a random prediction.
Finally, MCC = 0 would be expected for a random prediction scheme (Matthews, 1975).
Similar(56)
Particularly, the top-ranked combined centralities (AUC > 0.60) successfully identified essential genes in both KEGG and iND750 networks: the observed number of predictions (4 or more) for these 4 combined centralities is above the expected number in a random prediction for the 18 different networks tested (p = 0.01).
This graphical technique compares to a random prediction.
Another important consideration is whether the present prediction method is better than a random prediction.
The value of MCC is one for a perfect prediction, zero for a completely random prediction, and −1 for a perfectly inverse correlation.
It returns a value between −1 and +1: +1 stands for a perfect prediction, 0 for random prediction and −1 for totally reversed prediction.
A coefficient of +1 represents a perfect prediction, 0 an average random prediction and −1 an inverse prediction.
A coefficient equals to +1 indicates a perfect prediction; 0, an average random prediction; and (-1), an inverse prediction.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com