缩放和绑带

Raymond A. Anderson
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引用次数: 0

摘要

接下来是将代理和系数转换为可以计算成分数的点,这是沟通模型输出和实现所需要的。有两部分。(1)缩放- i)它意味着什么,为什么要这样做,以及期望的品质;Ii)百分比——为什么不呢?Iii)固定范围——指定最高值和最低值;Iv)缩放参数-使用基准分数和赔率,以及定点到双赔率;V)其他考虑-向非技术观众展示,以及不利的原因代码。(2) band - i)零约束-既不是组的数量,也不是每个组的风险;Ii)拟合分布——匹配指定的频率分布;iii)基准-给定的平均风险水平{AAA, AA+, AA,…C};Iv)固定频带边界-每个等级的上限和下限。最后两个选项适用于主评定量表,建议使用它们来确保组织内意义和沟通的一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scaling and Banding
Next is to convert proxies and coefficients into points that can be tallied into a score, which is needed for communicating model outputs, and implementation. There are two parts. (1) Scaling—i) what it means, why it’s done, and desired qualities; ii) percentages—why not; iii) fixed ranges—specify highest and lowest values; iv) scaling parameters—use of a benchmark score and odds, and fixed points-to-double odds; v) other considerations—presentation to a non-technical audience, and adverse reason codes. (2) Banding—i) zero constraints—neither the number of groups or risk of each; ii) fitted distributions—to match a specified frequency distribution; iii) benchmarked—to given average risk levels {AAA, AA+, AA, … C}; iv) fixed-band boundaries—upper and lower limits for each grade. The last two options are appropriate for Master Rating Scales, which are recommended to ensure consistency of meaning and communication within an organization.
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