Table 2

Classification statistics for each PCA model constructed.

Data type

Scaling

Sensitivity

Specificity

Correctly classified

Cross-validation accuracy


1D NMR, mussel muscle

unscaled

0.333

0.800

16 of 27

37.04%

autoscaled

0.083

0.933

15 of 27

33.33%

Pareto

0.500

0.733

17 of 27

51.85%

glog

1.000

1.000

27 of 27

100.00%

extended glog

1.000

0.86667

25 of 27

92.60%

pJRES NMR, dog urine

unscaled

0.294

0.750

20 of 37

32.43%

autoscaled

0.824

0.850

31 of 37

83.78%

Pareto

0.530

0.700

23 of 37

56.76%

glog

0.824

0.850

31 of 37

83.78%

extended glog

0.824

0.850

31 of 37

83.78%

2D JRES NMR, fish liver

unscaled

1.000

0.550

29 of 38

68.42%

autoscaled

0.944

0.800

33 of 38

63.16%

Pareto

0.944

0.800

33 of 38

86.84%

glog

0.889

0.850

33 of 38

86.84%

extended glog

1.000

1.000

38 of 38

100.00%


Parsons et al. BMC Bioinformatics 2007 8:234   doi:10.1186/1471-2105-8-234

Open Data