# Random sample of population sub sample size

I am generating models and each model is a random sample of the total model population. It is recommended that I generate 30,000 models and cluster taking the top 5 to 10 clusters to reach the native state.

I would like to adjust the 30,000 number lower but still remain within the probable range of the native structure. If $\Pr(\text{Native}\mid 30000)=1$; what is $\Pr(\text{Native}\mid X)$? I read about Bayesian statistics but I don't have all the pieces to put together Bayes' theorem for this problem. I also read about frequentist approach but I haven't used it before.

"Cluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more similar (in some sense or another) to each other than to those in other clusters."

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 That may just be me but I have hard time making sense of this question. Could you perhaps add some information: what are "cluster" and what is that "naive structure"? – chl♦ Oct 13 '12 at 19:35 @chi sorry about naive it was supposed to be native...and I added a definition of clustering – caseyr547 Oct 13 '12 at 22:27