Predicting Cardiovascular Risks using Pattern Recognition and Data ...

The SOM algorithm is applied to the input map to cluster the input data (see the results in Table 6.15).Assume that clusters “C1”; “C2”; “C3” correspond to the classes “High”; “Medium”; and “Low”respectively. According to Table 6.15, the accuracy rates are poor (less than 0.50). Figure 6.4 shows theclustering map where each generated cluster is coded by the black and white colour scale. The expectedlabelled risks can be seen in the map as in Figure 6.5 below. From Figure 6.4 and Figure 6.5, it issuggested that the cluster on the top left of clustering map (cluster 2) can be seen as the “Medium”cluster. This is because many “Medium” labels are distributed in this area (Figure 6.5).Figure 6.4: The clustering result for the map in Figure 6.2.100Figure 6.5: The labelled risks for the map in Figure 6.4.