New Statistical Algorithms for the Analysis of Mass - FU Berlin, FB MI ...

100 CHAPTER 4. (BIO-)MEDICAL APPLICATIONS
Training classifiers with fingerprint F1 we used 10-fold cross-validation to
measure the performance of these classifiers. The results are shown in Figure
4.5.16.
Training classifiers with fingerprint F2 we used 10-fold cross-validation to
measure the performance of these classifiers. The results are shown in Figure
4.5.17.
To show that the fingerprints are generalizable we then used the fingerprints
F1 and F2 to build classifiers that can distinguish between the TPO
and Tg antibody classes. Performance was again measured by the 10-fold
cross-validation schema. These results are shown in Figure 4.5.18.
Figure 4.5.16: Classification of the training set and test sets in 10-fold-stratified
cross-validation. Data is shown for four different classifiers using the fingerprint F1
after classification of n = 981 spectra “above 37.1 IU/mL TPO antibody” vs. “Control”.
Figure 4.5.17: Classification of the training set and test sets in 10-fold-stratified
cross-validation. Data is shown for four different classifiers using the fingerprint F2
after classification of n = 450 spectra “above 98.1 IU/mL Tg antibody” vs. “Control”.
Figure 4.5.18: Classification of the training set and test sets in 10-fold-stratified
cross-validation. Data is shown for four different classifiers using the fingerprints F1
& F2 after classification of n = 1097 spectra “above 37.1 IU/mL TPO antibody” vs.
“above 98.1 IU/mL Tg antibody”.