Fast and robust imputation for miRNA expression data using constrained least squares

BMC Bioinformatics

Table 4 Keller and Japan data results

Classification	AUC	F₁ score	ACC
(a) Classification results
Multiple sclerosis	.96	.85	.93
Melanoma	.97	.88	.93
HCC	.99	.93	.97
Bladder cancer	\(\sim 1\)	.97	.99

Classification	\(t_{\mu }\)	\(t_{\sigma }\)	\(t_M\)
(b) Imputation times
Multiple sclerosis	.008	.004	.102
Melanoma	.009	.006	.128
HCC	.273	.155	.922
Bladder cancer	.298	.161	1.15

(a) Mean values over curves shown in Fig. 9a–c. (b) Mean (\(t_\mu\)), standard deviation (\(t_\sigma\)), and maximum (\(t_{\text {max}}\)) imputation times (in seconds) over all test patients. In table (a), \(\sim 1\) indicates that the AUC is strictly greater than .995

ISSN: 1471-2105