Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

Table 14

Standard deviation measures for different algorithms in different datasets.

The standard deviation of each algorithm
Iris
Algorithm	Cluster1	Cluster2	Cluster3
K-means	1.847	1.7277	1.9847
C-ACO	1.9185	1.809	1.9742
C-Firefly	1.847	1.626	1.913
C-Cuckoo	1.847	1.7345	1.982
C-Bat	1.847	1.7311	1.9741
Wine
Algorithm	Cluster1	Cluster2	Cluster3
K-means	319.8828	194.4313	123.3868
C-ACO	296.27	155.166	154.7441
C-Firefly	319.8828	194.4315	123.3868
C-Cuckoo	319.8828	194.4315	123.383
C-Bat	318.5658	200.5721	130.7622
Haberman
Algorithm	Cluster1	Cluster2
K-means	28.1977	25.1797
C-ACO	28.019	25.4671
C-Firefly	28.0842	25.137
C-Cuckoo	28.1977	25.1797
C-Bat	28.1627	25.193