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pith:7XVDKBIS

pith:2026:7XVDKBISHLGOFDTDRKDLIY2LSC
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Aligning Validation with Deployment in Spatial Prediction: Target-Weighted Cross-Validation

Alexander Brenning, Thomas Suesse

Target-weighted cross-validation reduces bias in spatial prediction performance estimates by aligning validation tasks with the full deployment domain.

arxiv:2603.29981 v3 · 2026-03-31 · cs.LG · stat.ML

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\pithnumber{7XVDKBISHLGOFDTDRKDLIY2LSC}

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2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

weighted CV approaches substantially reduce this bias when validation tasks adequately cover the deployment-task space.

C2weakest assumption

That spatially meaningful task descriptors such as environmental covariates and prediction distance are sufficient to represent and cover the full deployment-task space for weighting purposes.

C3one line summary

Target-Weighted Cross-Validation reduces bias in spatial model performance estimates by weighting validation tasks to match the distribution of prediction tasks across the deployment domain.

Formal links

2 machine-checked theorem links

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1 paper in Pith

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First computed 2026-05-22T02:04:40.599562Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

fdea3505123acce28e638a86b4634b90a3edac010a92c4a79569157eac3e9eac

Aliases

arxiv: 2603.29981 · arxiv_version: 2603.29981v3 · doi: 10.48550/arxiv.2603.29981 · pith_short_12: 7XVDKBISHLGO · pith_short_16: 7XVDKBISHLGOFDTD · pith_short_8: 7XVDKBIS
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/7XVDKBISHLGOFDTDRKDLIY2LSC \
  | 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: fdea3505123acce28e638a86b4634b90a3edac010a92c4a79569157eac3e9eac
Canonical record JSON
{
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      "stat.ML"
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-03-31T16:44:07Z",
    "title_canon_sha256": "e68a6672ad0582c2858bcd7591ffbcd95748cdc7cd44887b2ff602f0527f6590"
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  "source": {
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    "kind": "arxiv",
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