Hi friends,
Please can someone give me the comparison between "Simulated Anneanling Algroithm" and "k-means Algorithm".On the other hand, i want the source code in C++ for each algorithm.
Thank you very much your help.
Best regards.
K-Means is a clustering algorithm, that is it identifies better groups in a data based on a loos function named as squared sum of errors (SSE). Simulated Annealing is a heuristic based search strategy or optimisation strategy, which approaches it probabilisticaly.
Thank you Sir Saptarsi for the answer.
Like k-means, SA minimizes the total sum of squared distance between all the non cluster head nodes and the closest cluster head. is it true or false?
Please, What can i do for to integre k-means in SA?
Thank you
Well SA, is more generic and can be applied for different optimisation algorithms. You may look at this paper http://www.sciencedirect.com/science/article/pii/003132039190097O. Rather than C++, you might want to use 'R', 'Matlab'.
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