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Exact(10)
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 best methods are able to achieve over 30% Top 1 ranks and most methods have the correct candidate in the Top 10 for around 50% of cases using fragmentation information alone, such that the outlook for higher-throughput untargeted annotation for "known unknowns" is very positive.
The 3rd best methods are ICA and SVM.
Similar(49)
The best methods were then validated in the human set-up.
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.
Simple "off-the-shelf" methods performed competitively with other more complex approaches, and the best methods were distinguished by which of the available data were used.
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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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