Average Case Performance Analysis
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With respect to the *mean* statistic, the following observations can be made:

-   [**Initial SSE**]{}: `OP` is the best method, followed closely by `P`, `OV`, and `V`. The remaining methods give $1.7$–$3.2$ times worse *mean* initial SSE than any of these hierarchical methods. Random methods exhibit significantly worse *average* performance than the deterministic ones because the former methods can produce highly variable results across different runs (see the standard deviation values in Table \[tab\_init\_sse\]).

-   [**Final SSE**]{}: This is similar to the case of *minimum* final SSE, with the difference that deterministic methods (except `X`) are now slightly better than the random ones. Once again, this is because random methods can produce highly variable results due to their stochastic nature.

-   [**Number of Iterations**]{}: The ranking of the methods is similar to the case of *mean* final SSE.

Consistency Analysis
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With respect to the *standard deviation* statistic, `F` is significantly better than both `M` and `K`. If, however, the application requires absolute consistency, i.e., exactly the same clustering in every run, a deterministic IM should be used.

CPU Time Analysis
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It can be seen from Table \[tab\_cpu\_time\] that, on about half of the 