Table 4 Size of the training dataset vs. execution times taken by the Prote2S and the SVM during the training process.
From: Prediction of protein secondary structures with a novel kernel density estimation based classifier
| Â | Prote2S | SVM | ||||
|---|---|---|---|---|---|---|
Number of protein chains used to generate the training dataset | Training time (in seconds) | Q3 | SOV | Training time (in seconds) | Q3 | SOV |
50 | 29.6 | 64.0% | 52.9% | 138.08 | 71.3% | 64.3% |
100 | 91.7 | 69.0% | 64.1% | 527.02 | 74.0% | 68.3% |
250 | 486.4 | 71.4% | 67.2% | 5105.63 | 75.5% | 71.0% |
500 | 1377.4 | 71.9% | 67.9% | 21040.0 | 76.8% | 72.3% |
1000 | 3887.8 | 73.9% | 71.1% | 78795.25 | 77.4% | 73.3% |