Table 1 Mean accuracy and standard error of the mean of various classifiers, using three features derived from the alignment of the sequences to be compared. 100-fold jackknife resampling was employed. "± " denotes the standard error of the mean.
From: IsoSVM – Distinguishing isoforms and paralogs on the protein level
SVM classifier | |||||
|---|---|---|---|---|---|
Accuracy | Precision | True Positives | True Negatives | False Positives | False Negatives |
99.55% ± 0.008 | 99.31% ± 0.015 | 1897.1 ± 0.21 | 1887.9 ± 0.28 | 13.1 ± 0.28 | 3.9 ± 0.21 |
RBF network classifier | |||||
Accuracy | Precision | True Positives | True Negatives | False Positives | False Negatives |
99.33% ± 0.011 | 98.91% ± 0.019 | 1896.5 ± 0.22 | 1880.1 ± 0.38 | 20.9 ± 0.38 | 4.6 ± 0.22 |
3-feature linear classifier | |||||
Accuracy | Precision | True Positives | True Negatives | False Positives | False Negatives |
99.42% ± 0.011 | 99.22% ± 0.020 | 1893.8 ± 0.35 | 1886.0 ± 0.39 | 15.0 ± 0.39 | 7.2 ± 0.35 |