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pith:7CPDXGPC

pith:2026:7CPDXGPCIUK5IMKDL5HMVGUKCG

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RoSHAP: A Distributional Framework and Robust Metric for Stable Feature Attribution

Boyu Jiang, Dawei Zhou, Feng Guo, Lanxin Xiang, Liang Shi, Youhui Ye

RoSHAP summarizes the distribution of SHAP values to rank features by their activity, strength, and stability simultaneously.

arxiv:2605.15154 v1 · 2026-05-14 · stat.ML · cs.LG

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Claims

C1strongest claim

We show that, under mild regularity conditions, the aggregated feature attribution score is asymptotically Gaussian, which greatly reduces the computational cost of distribution estimation. The RoSHAP summarizes the distribution of SHAP into a robust feature-ranking criterion that simultaneously rewards features that are active, strong, and stable.

C2weakest assumption

The mild regularity conditions under which the aggregated feature attribution score is asymptotically Gaussian.

C3one line summary

RoSHAP is a robust feature-ranking metric that summarizes the distributional properties of SHAP values via bootstrap resampling and asymptotic normality to reward active, strong, and stable features.

References

26 extracted · 26 resolved · 0 Pith anchors

[1] A unified approach to interpreting model predictions.Advances in neural information processing systems, 30 2017

[2] why should i trust you? 2016

[3] Learning important features through propa- gating activation differences 2017

[4] Explainable ai-based deep- shap for mapping the multivariate relationships between regional neuroimaging biomarkers and cognition 2024

[5] Practical guide to shap analysis: Explaining supervised machine learning model predictions in drug development.Clinical and translational science, 17(11):e70056, 2024 2024

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Receipt and verification

First computed	2026-05-17T21:40:25.447168Z
Last reissued	2026-05-17T21:57:18.769604Z
Builder	pith-number-builder-2026-05-17-v1
Signature	unsigned_v0
Schema	pith-number/v1.0

Canonical hash

f89e3b99e24515d431435f4eca9a8a11a0643ee84f3a02a32d26224dcb0761f6

Aliases

arxiv: 2605.15154 · arxiv_version: 2605.15154v1 · pith_short_12: 7CPDXGPCIUK5 · pith_short_16: 7CPDXGPCIUK5IMKD · pith_short_8: 7CPDXGPC

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/7CPDXGPCIUK5IMKDL5HMVGUKCG \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: f89e3b99e24515d431435f4eca9a8a11a0643ee84f3a02a32d26224dcb0761f6

Canonical record JSON

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    "license": "http://creativecommons.org/licenses/by/4.0/",
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