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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