Unverified50% confidenceFactExact time
The α-RC metrics are monotonic: metric values are non-decreasing with α.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
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Related Claims
UnverifiedThe α-RC metrics are bounded: regardless of network architecture, all α-RC metrics fall within the [0,1] interval; 0 means magnitude is uniformly distributed across all minors, and 1 means magnitude is entirely carried by a single minor.79% similarUnverifiedWhen α=2, α-RC reduces to an explicit transformation of the Participation Ratio, thereby eliminating scale dependence while retaining PR's interpretability.70% similarUnverifiedThe paper's authors propose a class of α-RC metrics based on Rényi divergence, which normalize the concentration measure to the [0,1] interval and are independent of network architecture.66% similarVerifiedIn highly imbalanced datasets (with a positive rate below 5%), the area under the precision-recall curve (AP) often reflects the model's ability to detect the minority class better than AUC does.66% similarUnverifiedWhen α=β=1, the Beta distribution degenerates into a uniform distribution; when α,β<1, it exhibits a U-shape.65% similar
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