Research Article
Recognition of 27-Class Protein Folds by Adding the Interaction of Segments and Motif Information
Table 4
The previous identification results by an independent test from Ding and Dubchak’s dataset (%).
| | Author | Classifier | Accuracy |
| | Ding and Dubchak [11] | SVM (All-Versus-All) | 56.0 | | Chinnasamy et al. [12] | Tree-Augmented Naive Bayesian Classifier | 58.2 | | Shen and Chou [21] | OET-KNN | 62.1 | | Nanni [13] | Fusion of classifiers | 61.1 | | Chen and Kurgan [22] | PFRES | 68.4 | | Guo and Gao [14] | GAOEC | 64.7 | | Damoulas and Girolami [15] | Multiclass multikernel | 70.0 | | Zhang et al. [20] | Increment of diversity | 61.1 | | Ghanty and Pal [23] | Fusion of different classifiers | 68.6 | | Dong et al. [18] | ACCFold | 70.1 | | Shen and Chou [24] | PFP-FunDSeqE | 70.5 | |
Yang et al. [25] | MarFold | 71.7 | | Liu et al. [27] | SVM | 69.8 | | Our work | Random Forest | 70.2 |
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