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The conditional posterior probabilities are computed at the block denoted as "GMM", and the decision is made using the ML rule (9). Figure 7 Scheme of the proposed classifier.
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Majority rule (50%) consensus trees were constructed using the Ml methods [ 33].
Majority rule (50%) consensus trees were constructed using the Ml methods [ 22] and the tree was viewed using TreeView [ 23].
After the candidates are generated, lists are built for each group of users, and the ML rule is used to choose the best candidate list as described by textbf{b}^{text{best}}(i)= {text{arg}}min_{substack{1leq jleq N_{c}^{n_{q}} text{or} {N_{c}^{n}}}}parallel textbf{y}_{text{sr}_{l}}(i -textbf{H}_{text{sr}_{l}}(i -textbf{}^{j}(i)parallel^{2}, (21).
Data are fused using the sum rule.
Areas under the curve (AUC in ng/mL × min) of unbound quinidine in plasma from 0 to 240 min after administration (AUCPLu,0 240) were calculated using the trapezoidal rule.
iAUC was calculated using the trapezoidal rule.
AUC was computed using the trapezoidal rule.
Dominance-based decision rules were extracted using the VC-DomLEM rule induction algorithm.
The ML tree generation used a BLOSUM62 matrix and the consensus tree shown in Fig. 2 was generated using the extended majority rule of RAxML.
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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