Research Article
Motif-Based Text Mining of Microbial Metagenome Redundancy Profiling Data for Disease Classification
Table 2
Classification results of pneumonia data in 3-class problem.
| Method | Error rate | Dimension |
Feature | On training data | On test data |
| SVM/FMS | 0.1895 | 0.2637 | 29 | Microbes | SVM/PMF | 0.062 | 0.0756 | 411 | Sequences | SVM/Kruskal-Wallis | 0.1187 | 0.5273 | 272 | Sequences | SVM/Information Gain | 0.143 | 0.2124 | 12 | Sequences | SVM/Chi-square statistic | 0.1743 | 0.5909 | 1280 | Sequences | SVM | 0.2187 | 0.3812 | 4390 | Sequences | NNA/FMS | 0.2013 | 0.3406 | 112 | Microbes | NNA/PMF | 0.2152 | 0.2081 | 786 | Sequences | NNA/Kruskal-Wallis | 0.2718 | 0.3363 | 85 | Sequences | NNA/Information Gain | 0.2354 | 0.4141 | 39 | Sequences | NNA/Chi-square statistic | 0.2649 | 0.3107 | 69 | Sequences | NNA | 0.442 | 0.6162 | 4390 | Sequences |
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