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Fuzzy Classification Aggregation for a Continuum of Agents

Created by
  • Haebom

Author

Zijun Meng

Outline

This paper proves that the optimal, independent, and 0-unanimous fuzzy classification aggregate function for a continuous discrete classifier that classifies $m \ge 3$ objects into $2 \le p \le m$ types must be the weighted arithmetic mean.

Takeaways, Limitations

Takeaways: Provides a theoretical basis for designing and analyzing fuzzy classification models by clearly proposing the optimal functional form under specific conditions of the fuzzy classification aggregate function. It provides mathematical support for the justification of using the weighted arithmetic mean.
Limitations: Whether the conditions used in the proof (optimality, independence, 0-unanimity) are applicable to all fuzzy classification problems requires further study. The appropriateness of these conditions should be examined in real applications. Whether the constraints on $m$ and $p$ ($m \ge 3$, $2 \le p \le m$) can be relaxed requires further study.
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