Table 3 Classification metrics for training and test set.

From: Novel ratio-metric features enable the identification of new driver genes across cancer types

   

Accuracy

F1 score

Precision

Recall

cTaG

Training set

OG

0.86 ± 0.04

0.77 ± 0.07

0.93 ± 0.04

0.67 ± 0.09

TSG

0.90 ± 0.03

0.84 ± 0.04

0.97 ± 0.01

Test set

OG

0.76 ± 0.03

0.59 ± 0.10

0.79 ± 0.12

0.50 ± 0.19

TSG

0.83 ± 0.02

0.77 ± 0.07

0.91 ± 0.07

BalancedBagging

Training set

OG

0.93 ± 0.05

0.92 ± 0.06

0.86 ± 0.09

0.99 ± 0.01

TSG

0.94 ± 0.04

1.00 ± 0.01

0.90 ± 0.07

Test set

OG

0.69 ± 0.06

0.64 ± 0.06

0.56 ± 0.07

0.75 ± 0.06

TSG

0.73 ± 0.06

0.82 ± 0.04

0.65 ± 0.09

  1. Numbers in bold indicate best performances for each metric between TSG and OG. The metrics are standard, and are defined as follows (T stands for True, F for false, P for positives and N for negatives): Accuracy = (TP + TN)/(TP + FP + TN + FN); Precision = TP/(TP + FP); Recall = TP/(TP + FN); F1 score is the harmonic mean of Precision and Recall.
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