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Table 1 Handwritten image data results

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

Metric FLI VIPER scImpute Regression Mean Zeros
(a) Classification results
AUC \(\sim\)1 \(\sim\)1 .98 .96 .97 .96
\(F_1\) .99 .99 .98 .93 .87 .83
ACC .99 .99 .98 .93 .90 .76
(b) Imputation errors
\(\epsilon _{\mu }\) .15 .15 .35 .71 .59 .68
\(\epsilon _{\sigma }\) .08 .10 .55 .32 .07 .04
\(\epsilon _{M}\) .53 .70 6.2 2.4 .93 .81
Time FLI VIPER scImpute Regression Mean Zeros
(c) Imputation time
\(t_\mu\) .106 11.0 5.21 .126 \(\sim\)0 \(\sim\)0
\(t_\sigma\) .066 5.47 2.42 .122 \(\sim\)0 \(\sim\)0
\(t_{\text {max}}\) .346 33.8 14.6 1.23 \(\sim\)0 \(\sim\)0
  1. a Mean values over curves shown in Fig. 2a–c. b Mean values over curves shown in Fig. 2d–f. c 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 than .995. In table (c), \(\sim 0\) indicates the imputation time is strictly less than .0005 s