L2-norm multiple kernel learning and its application to biomedical data fusion

BMC Bioinformatics

Table 8 Results of experiment 4 data set I: classification of endometrial disease patients using multiple kernels derived from clinical data

Classifier	Mean - error of AUC	Std. - error of AUC	pvalue
LSSVM L _∞ (0.5) MKL	0.2353	0.0133	-
SVM L _∞ (0.5) MKL	0.2388	0.0178	0.4369
SVM L _∞ MKL	0.2417	0.0165	0.2483
LSSVM L₂ MKL	0.2456	0.0124	0.0363
SVM L₂ MKL	0.2489	0.0178	0.0130
SVM L₁ MKL	0.2513	0.0144	0.0057
LSSVM L₁ MKL	0.2574	0.0189	9.98 · 10^-5
LSSVM L_∞ MKL	0.2678	0.0130	1.53 · 10^-6

Results of experiment 4 data set I: classification of endometrial disease patients using multiple kernels derived from clinical data. The classifier with the best performance is shown in bold. The p-values are compared with the best performance using a paired t-test. The performance of classifiers is sorted from high to low according to the p-values.

ISSN: 1471-2105