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The Clark method performed the best overall among the selected models, with both NEC and R2 values greater than 0.95.
The ANFIS method performed the best on average and the final models displayed the highest R2 and lowest mean squared error (MSE) for FamilyIBI (R2 = 0.50, MSE = 29.80), HBI (R2 = 0.57, MSE = 0.20), and EPTtaxa (R2 = 0.54, MSE = 6.60).
The reported results show that the third method performed the best in recommending hashtags.
The TCA method performed the best followed by the Huang [51] approach and the Blitzer [5] approach.
The DTMKL method performed the best for all applications, and the baseline approach is consistently the worst performing.
Since they reported that this method performed the best when (X=5) and (Y=50), we used the same numbers for these parameters in our experiment.
Similar(28)
This method performs the same calculation as mytsearch above, but only on those pixels inside the bounding box of the polygon.
It shows that our construction method performs the best.
Finally, the proposed method performs the better results than the other method in the experiments.
In particular, the proposed method performs the best visual result comparing to other methods.
The average results show the upper bound method performing the best and the Prettenhofer [91] method performing better than the baseline method.
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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