Selected article for: "AUC score and cross validation"
Author: Yujia Xiang; Quan Zou; Lilin Zhao
Title: VPTMdb: a viral post-translational modification database
  • Document date: 2020_4_2
    • ID: kl99afiu_57
    Snippet: The data in Table 2 show that six features as well as their combinations were evaluated in SVM with a 5-fold cross-validation. AUC, F1-score and MCC were used as the performance evaluation indicators. The results declare that the z-scale, which captures the physical-chemical in-formation of amino acids, is the best among the six single features (AUC=0.957, F1-Score=0.887, MCC=0.810). For BINARY, EGAAC and CTriad, their AUC values also achieved ab.....
    Document: The data in Table 2 show that six features as well as their combinations were evaluated in SVM with a 5-fold cross-validation. AUC, F1-score and MCC were used as the performance evaluation indicators. The results declare that the z-scale, which captures the physical-chemical in-formation of amino acids, is the best among the six single features (AUC=0.957, F1-Score=0.887, MCC=0.810). For BINARY, EGAAC and CTriad, their AUC values also achieved above 90.00%. Moreover, when we fused the features, the result showed that ZSCALE combined author/funder. All rights reserved. No reuse allowed without permission.

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