Table 4

Performance evaluation in terms of sensitivity and specificity
Sensitivity Specificity
# of terms SVM Logistic Ridge SVM Logistic Ridge
10 0.6211 ± 0.020 0.6267 ± 0.023 0.6307 ± 0.020 0.8520 ± 0.012 0.8460 ± 0.012 0.8323 ± 0.012
20 0.4633 ± 0.020 0.4483 ± 0.020 0.4441 ± 0.017 0.9252 ± 0.006 0.9354 ± 0.006 0.9309 ± 0.006
30 0.3306 ± 0.025 0.3154 ± 0.023 0.3038 ± 0.019 0.9523 ± 0.004 0.9566 ± 0.004 0.9573 ± 0.004
40 0.2549 ± 0.015 0.2424 ± 0.014 0.2320 ± 0.012 0.9628 ± 0.003 0.9677 ± 0.003 0.9668 ± 0.003
50 0.2032 ± 0.012 0.1974 ± 0.011 0.1910 ± 0.012 0.9724 ± 0.003 0.9732 ± 0.003 0.9723 ± 0.003

Sparse feature is used and the classification performance on stage range 11-12 is reported. Three different classifiers are applied for comparison, namely, SVM with linear kernel (SVM), logistic regression (Logistic) and ridge regression (Ridge).

Yuan et al.

Yuan et al. BMC Bioinformatics 2012 13:107   doi:10.1186/1471-2105-13-107

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