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:
政绩观，连着发展观。政绩观正确与否，决定着发展的成效乃至成败。
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Third: Keep it Untouchable (Object.defineProperty)