FIGURE 3 Age group division. The bars represent number of
subjects in each age group, while the colours illustrate the
within-class gender distribution.
2.3.2 | Classification to age groups with variable age group
thresholds
The effect of varying the age group thresholds was further analysed. Age
grid of 26 to 63 was used to evaluate different thresholds. Instead of
using all the ages between minimum and maximum in the age grid, only the
ages appearing in the data were considered as part of the grid. As a
result, the best corresponding thresholds were found for each classifier
based on the achieved balanced accuracy. For each threshold, stratified
K-fold CV was used with K=5. Figure 4 illustrates the age threshold
finding process for each test.
In the age threshold test 1, all the data was used and split into two
age groups of young and old adults using the aforementioned age grid.
For the test 2, two age thresholds were used and the in-between data was
excluded from the ML pipeline, while the beyond threshold subjects were
sorted in to young and old adult groups. Test 3 used similar method as
test 2, but the in-between data was used as a third rejection class. The
goal of the tests 2 and 3 was to identify how the exclusion or inclusion
of the in-between groups affects the classifiers performance.