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The 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.
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10/19/2026
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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% similarUnverifiedThe authors introduce a normalized MPE taking values in the unit interval [0, 1] as a dimensionless measure of predictive efficiency.69% similarUnverifiedLayer normalization standardizes each sample across the feature dimension to zero mean and unit variance68% similarUnverifiedThe α-RC metrics are monotonic: metric values are non-decreasing with α.66% similarUnverifiedIC通常用Pearson相关系数计算，取值范围-1到1，日均IC稳定达到0.03-0.05即被认为具有统计意义，顶级因子也很少超过0.165% similar
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