{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:JYJB6GZ44G4AASVUMO2EOAEWBX","short_pith_number":"pith:JYJB6GZ4","schema_version":"1.0","canonical_sha256":"4e121f1b3ce1b8004ab463b44700960dda572146d97e0a1bcd26d5d7ef32d8dc","source":{"kind":"arxiv","id":"1702.08694","version":3},"attestation_state":"computed","paper":{"title":"Finding Statistically Significant Interactions between Continuous Features","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Karsten Borgwardt, Mahito Sugiyama","submitted_at":"2017-02-28T08:46:37Z","abstract_excerpt":"The search for higher-order feature interactions that are statistically significantly associated with a class variable is of high relevance in fields such as Genetics or Healthcare, but the combinatorial explosion of the candidate space makes this problem extremely challenging in terms of computational efficiency and proper correction for multiple testing. While recent progress has been made regarding this challenge for binary features, we here present the first solution for continuous features. We propose an algorithm which overcomes the combinatorial explosion of the search space of higher-o"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1702.08694","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-02-28T08:46:37Z","cross_cats_sorted":["cs.LG","stat.ME"],"title_canon_sha256":"843a7483234429ff69e5d7ddb291543f3b97014e5b3f9c5ddcef4c8715cb10f4","abstract_canon_sha256":"ec8866b060a3fb12ed07190862dce66974e5575bc73926d3ed3e25febd22c736"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:46:32.157298Z","signature_b64":"IzhVIGVJInsN13+Cp4CrFB+pTtl4tgvKyHpw86yEordRhqr9UDed0onfqaCyxhmXWTHkNj91X6+NgekTtHuWDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e121f1b3ce1b8004ab463b44700960dda572146d97e0a1bcd26d5d7ef32d8dc","last_reissued_at":"2026-05-17T23:46:32.156732Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:46:32.156732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Finding Statistically Significant Interactions between Continuous Features","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Karsten Borgwardt, Mahito Sugiyama","submitted_at":"2017-02-28T08:46:37Z","abstract_excerpt":"The search for higher-order feature interactions that are statistically significantly associated with a class variable is of high relevance in fields such as Genetics or Healthcare, but the combinatorial explosion of the candidate space makes this problem extremely challenging in terms of computational efficiency and proper correction for multiple testing. While recent progress has been made regarding this challenge for binary features, we here present the first solution for continuous features. We propose an algorithm which overcomes the combinatorial explosion of the search space of higher-o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.08694","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1702.08694","created_at":"2026-05-17T23:46:32.156831+00:00"},{"alias_kind":"arxiv_version","alias_value":"1702.08694v3","created_at":"2026-05-17T23:46:32.156831+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.08694","created_at":"2026-05-17T23:46:32.156831+00:00"},{"alias_kind":"pith_short_12","alias_value":"JYJB6GZ44G4A","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_16","alias_value":"JYJB6GZ44G4AASVU","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_8","alias_value":"JYJB6GZ4","created_at":"2026-05-18T12:31:24.725408+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX","json":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX.json","graph_json":"https://pith.science/api/pith-number/JYJB6GZ44G4AASVUMO2EOAEWBX/graph.json","events_json":"https://pith.science/api/pith-number/JYJB6GZ44G4AASVUMO2EOAEWBX/events.json","paper":"https://pith.science/paper/JYJB6GZ4"},"agent_actions":{"view_html":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX","download_json":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX.json","view_paper":"https://pith.science/paper/JYJB6GZ4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1702.08694&json=true","fetch_graph":"https://pith.science/api/pith-number/JYJB6GZ44G4AASVUMO2EOAEWBX/graph.json","fetch_events":"https://pith.science/api/pith-number/JYJB6GZ44G4AASVUMO2EOAEWBX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX/action/storage_attestation","attest_author":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX/action/author_attestation","sign_citation":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX/action/citation_signature","submit_replication":"https://pith.science/pith/JYJB6GZ44G4AASVUMO2EOAEWBX/action/replication_record"}},"created_at":"2026-05-17T23:46:32.156831+00:00","updated_at":"2026-05-17T23:46:32.156831+00:00"}