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In contrast with the use of frame level features, Ramirez et al. [12] proposed the use of a long-term spectral divergence feature to discriminate speech from noise.
To investigate this we plotted LD 13), the divergence feature with the highest information gain, against Hphob, #neg and the arginine composition (the three highest scoring standard features in the 40 residue N-terminal region).
As shown in Table 6, in this experiment the divergence feature only performance (63%) is much higher than the majority class fraction (33%), and the divergence features also contribute more to the performance when combined with the standard features (Table 6).
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Card was not present at the film's appearance at Comic Con in San Diego last night, despite the panel for Lionsgate's other teen-orientated sci-fi flick, Divergence, featuring source novel author Veronica Roth.
The prediction result of 43 proteins changed depending on whether divergence features were added to conventional features.
In this experiment, divergence features improved the performance only slightly when combined with other standard features (Table 7).
In this section we discuss proteins for which the use of divergence features strongly affects the results.
To investigate this, we ranked instances whose SVM prediction changes drastically depending on whether or not divergence features are used.
Hopefully future work will clarify if this is another case in which divergence features flagged misannotations in our dataset.
IMO32 is predicted as an MTS by Predator [ 35] and our SVM when we use divergence, but not by our SVM without divergence features, nor by TargetP [ 61].
MrpL32 shows a high divergence in its N-terminal region and is predicted to have an MTS by our SVM when using divergence features.
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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