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Table 1 Experiment input data summary

From: A novel generative adversarial networks modelling for the class imbalance problem in high dimensional omics data

Experiment ID

Number of control samples

Class imbalance

1

40

0.4

2

80

0.4

3

120

0.4

4

40

0.5

5

80

0.5

6

120

0.5

7

40

0.6

8

80

0.6

9

120

0.6

  1. Table summarising the number of control samples and class imbalance for each experiment. Class imbalance is multiplied by the number of control samples to define the number of samples in the other class