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Figure 3 | BMC Bioinformatics

Figure 3

From: Incremental genetic K-means algorithm and its application in gene expression data analysis

Figure 3

The impacts of mutation probability on convergence for IGKA and FGKA. The population size is set to 50; the generation size is set to 100. The mutation probability ranges from 0.001 to 0.1 for fig2data, and 0.0001 to 0.1 for chodata. (A) shows the convergence with different mutation probability for FGKA and IGKA on fig2data. (B) shows the convergence with different mutation probability for FGKA and IGKA on chodata. These two algorithms have similar convergence results. When the mutation probability changes in these two data sets, it has little impact on two algorithms during the range that is given in the Figure, except for the case when the mutation probability is too large. It gives an opportunity to choose IGKA with better performance without losing the convergence benefit.

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