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Fig. 1 | BMC Bioinformatics

Fig. 1

From: Stepwise iterative maximum likelihood clustering approach

Fig. 1

An illustration of stepwise iterative maximum likelihood method using a c = 2 cluster case. In this illustration, two clusters and are given with likelihood functions L1 and L2, respectively. The center of clusters are depicted by μ 1 and μ 2 (shown as ‘+’ inside two clusters). Initial total likelihood is Lold which is the sum of two likelihood functions (L1 + L2). A sample \( \mathrm{x}\in \) is checked for grouping. It is advantageous to shift sample \( \mathrm{x} \) to cluster only if the new likelihood (Lnew = L *1  + L *2 ) is higher than the old likelihood; i.e., L new  > L old

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