Decisions using the kNN framework are arrived at through a majority vote of an observation’s k nearest neighbors (given some distance metric). When aggregating many kNN decisions and weighing them against one much more important kNN decision, one strategy I’ve found to work well is to copy congress:

The critical neighbor is “the President” and can’t “pass” the vote, but can “veto” it.
A decision is made to “pass” either on the vote of a majority of the neighbors in the absence of a veto, or given a 2/3 majority in its presence.

One example of this is aggregating decisions over a market index. Each individual asset in the index has an impact in its overall movement, but the index itself (the President) can also be analyzed directly.