- The value distribution curves of the reference patients or experiments
(fig.3a) are used for the determination of reference percentiles (fig.3b).
The numeric values of data columns are then transformed for classification purposes
into triple matrix characters (0), (+), (-) depending of their
location between, above or below the calculated upper and lower percentile
threshold (see between fig.3a/3b). This is done for all numbers of a given
data column that is for reference (fig.3a) as well as for the abnormal
group data (fig.3c)
- The operation results in a triple matrix database
suitable for data pattern classification with the CLASSIF1 algorithm.
- Symmetric percentile thresholds between 1 - 99%, 5 - 95%, 10 -90%,
15 - 85%, 20 - 80%, 25 - 75% or 30 - 70% are typically used to determine
the optimally discriminating percentile pair.
- Data classification > fig.3d
can be performed by using either the optimal percentile pair
for the classification of all data columns or by combining the optimal
percentile pair of each data column.