Based on a synthetic example, we illustrated that the micro-averaged silhouette score for evaluating clustering solutions suffers from two key weaknesses due to its sensitivity to cluster imbalance and background noise. By contrast, as we show, the macro-averaged silhouette is robust to both these issues.
Jan 15, 2024
Jan 11, 2024 · Silhouette coefficient is an established internal clustering evaluation measure that produces a score per data point, assessing the quality of its clustering ...
ABSTRACT. Silhouette coefficient is an established internal clustering evaluation measure that produces a score per data point, assessing the quality of its ...
Revisiting Silhouette: From Micro to Macro Aggregation. https://t.co/LZQHCMyltY.
Jun 25, 2024 · In this paper, the authors explore how Silhouette can be aggregated from the micro (individual data points) to the macro (entire dataset) level.
Silhouette aggregation revisited: A study of the Silhouette Coefficient when it is micro- and macro-averaged to assess clustering solutions. Silhouette ...
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We develop a new framework for aggregating from micro to macro patterns of trade. We derive price indexes that determine comparative advantage across countries ...
Missing: Silhouette | Show results with:Silhouette
Silhouette coefficient is an established internal clustering evaluation measure that produces a score per data point, assessing the quality of its ...
Session 1: Micro and macro views on financial stability: different perspectives of the risks affecting financial system. Macroprudential policy frameworks ...
In a multi-class classification setup with highly imbalanced classes, micro-averaging is preferable over macro-averaging. In such cases, one can alternatively ...