Approach to Data Clustering Based on Molecular Chemical Reactions With Various Distance Measures
Table 1: Objective function value summarized after 30 attempts. Synthetic (artificial) dataset
Parameter |
k-means |
KCR |
EuD |
SEuD |
ManD |
EuD |
SEuD |
ManD |
min |
100.2318 |
100.2318 |
102.5189 |
100.2318 |
100.2318 |
102.4449 |
max |
100.2379 |
100.2379 |
160.385 |
100.2379 |
100.2369 |
159.8675 |
mean |
100.2351 |
100.2353 |
115.9838 |
100.2334 |
100.2334 |
115.8819 |
σ |
0.003029 |
0.002945 |
24.29265 |
0.001683 |
0.001787 |
24.15255 |
V |
0.003021 |
0.002938 |
20.94486 |
0.001679 |
0.001783 |
20.84239 |
R |
0.006071 |
0.006071 |
57.86609 |
0.006071 |
0.00513 |
57.42261 |
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