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. 2018 Mar 16;9:476. doi: 10.3389/fmicb.2018.00476

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Copyright © 2018 Manavalan, Shin and Lee.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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(A) Performance of SVM-based classifiers in distinguishing between PVPs and non-PVPs. A total of 25 classifiers were evaluated using LOOCV, and their performances in terms of MCC, accuracy, sensitivity, and specificity are shown. The red arrow denotes the final selected model. (B) Classification accuracy of the F136-based (final selected) model with respect to variations in parameters C and γ. (C) Distribution of each feature type in the optimal feature set (136 features) and original feature set (583 features).