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Permutation Feature Importance Disruption Guarantee #320

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DarioS opened this issue Mar 22, 2022 · 0 comments
Open

Permutation Feature Importance Disruption Guarantee #320

DarioS opened this issue Mar 22, 2022 · 0 comments

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@DarioS
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DarioS commented Mar 22, 2022

Section 8.5 has

... we permuted the feature’s values, which breaks the relationship between the feature and the true outcome.

However, I think that permutation could rarely end up with a similar distribution of per-class measurements as the original data and hide the performance loss. Would a more robust method be to calculate the mean of a feature and set all samples to that value?

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