{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:IPIJBVYT7S5L73P5NH6OB2SPRU","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"ad5255d62b21aaf884566e0ea34aedc86d5bc3be1d0cf036a53b2bdefc5a45da","cross_cats_sorted":["stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-02-15T11:52:14Z","title_canon_sha256":"09a2545ef7f7104f77b82cf697050361343cb657764cd82978a2b4d3dc3892d0"},"schema_version":"1.0","source":{"id":"1702.04561","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.04561","created_at":"2026-05-18T00:50:41Z"},{"alias_kind":"arxiv_version","alias_value":"1702.04561v1","created_at":"2026-05-18T00:50:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.04561","created_at":"2026-05-18T00:50:41Z"},{"alias_kind":"pith_short_12","alias_value":"IPIJBVYT7S5L","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"IPIJBVYT7S5L73P5","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"IPIJBVYT","created_at":"2026-05-18T12:31:21Z"}],"graph_snapshots":[{"event_id":"sha256:de253df084560f390aeed43f3dfc27114869532df041814e47eab02a39565192","target":"graph","created_at":"2026-05-18T00:50:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We present a new variable selection method based on model-based gradient boosting and randomly permuted variables. Model-based boosting is a tool to fit a statistical model while performing variable selection at the same time. A drawback of the fitting lies in the need of multiple model fits on slightly altered data (e.g. cross-validation or bootstrap) to find the optimal number of boosting iterations and prevent overfitting. In our proposed approach, we augment the data set with randomly permuted versions of the true variables, so called shadow variables, and stop the step-wise fitting as soo","authors_text":"Andreas Mayr, Bernd Bischl, Janek Thomas, Tobias Hepp","cross_cats":["stat.CO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-02-15T11:52:14Z","title":"Probing for sparse and fast variable selection with model-based boosting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.04561","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:6db3303024419ab1f47bb4a6b3147b9417c666b753eadac8c72fe99a730219be","target":"record","created_at":"2026-05-18T00:50:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"ad5255d62b21aaf884566e0ea34aedc86d5bc3be1d0cf036a53b2bdefc5a45da","cross_cats_sorted":["stat.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-02-15T11:52:14Z","title_canon_sha256":"09a2545ef7f7104f77b82cf697050361343cb657764cd82978a2b4d3dc3892d0"},"schema_version":"1.0","source":{"id":"1702.04561","kind":"arxiv","version":1}},"canonical_sha256":"43d090d713fcbabfedfd69fce0ea4f8d338d2068b1319b90b091547844e6feed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"43d090d713fcbabfedfd69fce0ea4f8d338d2068b1319b90b091547844e6feed","first_computed_at":"2026-05-18T00:50:41.281996Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:50:41.281996Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LK7S8ZGnFrTeBzJba/i6sD05QSgdx38fPyu0JjbNOoggEp3aBpmTbl4cNommtYTGTTCzKkB1AawlSSwHRH1cDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:50:41.282700Z","signed_message":"canonical_sha256_bytes"},"source_id":"1702.04561","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6db3303024419ab1f47bb4a6b3147b9417c666b753eadac8c72fe99a730219be","sha256:de253df084560f390aeed43f3dfc27114869532df041814e47eab02a39565192"],"state_sha256":"367991dd0242f1d7ab08005e1c3ba5f4ee68f0f097b48e55cd57f8b9be75588a"}