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Table 2 Confusion matrixes for synthetic data sets

From: Principal component analysis based unsupervised feature extraction applied to budding yeast temporally periodic gene expression

A 1 2 3
PCA P≥0.01 P<0.01 P≥0.01 P<0.01 P≥0.01 P<0.01
i>100 9900 0 9900 0 9900 0
i≤100 0 100 0 100 0 100
Regression P≥0.01 P<0.01 P≥0.01 P<0.01 P≥0.01 P<0.01
i>100 9900 0 9900 17 9900 48
i≤100 0 100 0 83 0 52
A 4 5 6
PCA P≥0.01 P<0.01 P≥0.01 P<0.01 P≥0.01 P<0.01
i>100 9900 0 9900 0 9900 0
i≤100 0 100 0 100 0 100
Regression P≥0.01 P<0.01 P≥0.01 P<0.01 P≥0.01 P<0.01
i>100 9900 64 9900 72 9900 85
i≤100 0 36 0 28 0 15
  1. P-values were adjusted by BH criterion