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The best methods were then validated in the human set-up.
The best methods were able to achieve over 30% Top 1 ranks in Category 2, with all methods ranking the correct candidate in the Top 10 in around 50% of challenges.
On the basis of a previous comparison of various Tm prediction methods, it was observed that the best methods were the Nearest Neighbor methods based on thermodynamic properties, but the major drawback with these methods was that they applied well primarily to oligomers ranging from 4 to 20 bp [37].
The second best methods were FFP and kmacs with k = 3, 4 and 64 ≤ k ≤ 117.
For the other two datasets, GSE36700 and E-GEOD-29746, the best methods were IBk and SVM.
Anyhow, the fact that so many "best methods" were published in a single year clearly underlines that the field is immature.
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Next best methods are supervised learners KNN and Gaussian NB.
The best methods are those which involve pressing the layered sample in KBr pellets.
These best methods are used to acquire the final results in the fourth step.
The performance of each method is quantified and compared based on three norms and the best methods are identified.
The 3rd best methods are ICA and SVM.
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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