Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:
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BSA的長期年度調查發現：2018年，有12%的受訪者自稱基督徒，並至少每月上教堂一次；2024年則下降到9%。皮尤研究中心的分析則顯示，18–34歲的年輕族群更低，從8%降到6%。