{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:TDWSSZPKCPXL6CZ7RUBME2PDE6","short_pith_number":"pith:TDWSSZPK","schema_version":"1.0","canonical_sha256":"98ed2965ea13eebf0b3f8d02c269e3279fe4da5ed0e1a7a4a30a6ec632dbed1a","source":{"kind":"arxiv","id":"1306.6677","version":6},"attestation_state":"computed","paper":{"title":"Supersparse Linear Integer Models for Interpretable Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ML","authors_text":"Berk Ustun, Cynthia Rudin, Stefano Trac\\`a","submitted_at":"2013-06-27T22:42:01Z","abstract_excerpt":"Scoring systems are classification models that only require users to add, subtract and multiply a few meaningful numbers to make a prediction. These models are often used because they are practical and interpretable. In this paper, we introduce an off-the-shelf tool to create scoring systems that both accurate and interpretable, known as a Supersparse Linear Integer Model (SLIM). SLIM is a discrete optimization problem that minimizes the 0-1 loss to encourage a high level of accuracy, regularizes the L0-norm to encourage a high level of sparsity, and constrains coefficients to a set of interpr"},"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":"1306.6677","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-06-27T22:42:01Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"14cefb2eb9953a20ffe18a75b53a71bfa336e52b958bf20a33729699b8b81a56","abstract_canon_sha256":"d2a98907c67dc380519e24024cb2355c0c31d2ab2b44ca04a7ee8b1d1bb97f0a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:54:28.097457Z","signature_b64":"Lx2eDyfEmu3LafOM10AL6uzgf7lKGQOtBN71nOuAsbQc1yvwpyw4Tv8nWyJB7mU/uHOpqkjdpjH5X82qJb22DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"98ed2965ea13eebf0b3f8d02c269e3279fe4da5ed0e1a7a4a30a6ec632dbed1a","last_reissued_at":"2026-05-18T02:54:28.096812Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:54:28.096812Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Supersparse Linear Integer Models for Interpretable Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ML","authors_text":"Berk Ustun, Cynthia Rudin, Stefano Trac\\`a","submitted_at":"2013-06-27T22:42:01Z","abstract_excerpt":"Scoring systems are classification models that only require users to add, subtract and multiply a few meaningful numbers to make a prediction. These models are often used because they are practical and interpretable. In this paper, we introduce an off-the-shelf tool to create scoring systems that both accurate and interpretable, known as a Supersparse Linear Integer Model (SLIM). SLIM is a discrete optimization problem that minimizes the 0-1 loss to encourage a high level of accuracy, regularizes the L0-norm to encourage a high level of sparsity, and constrains coefficients to a set of interpr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1306.6677","kind":"arxiv","version":6},"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":"1306.6677","created_at":"2026-05-18T02:54:28.096911+00:00"},{"alias_kind":"arxiv_version","alias_value":"1306.6677v6","created_at":"2026-05-18T02:54:28.096911+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1306.6677","created_at":"2026-05-18T02:54:28.096911+00:00"},{"alias_kind":"pith_short_12","alias_value":"TDWSSZPKCPXL","created_at":"2026-05-18T12:28:02.375192+00:00"},{"alias_kind":"pith_short_16","alias_value":"TDWSSZPKCPXL6CZ7","created_at":"2026-05-18T12:28:02.375192+00:00"},{"alias_kind":"pith_short_8","alias_value":"TDWSSZPK","created_at":"2026-05-18T12:28:02.375192+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/TDWSSZPKCPXL6CZ7RUBME2PDE6","json":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6.json","graph_json":"https://pith.science/api/pith-number/TDWSSZPKCPXL6CZ7RUBME2PDE6/graph.json","events_json":"https://pith.science/api/pith-number/TDWSSZPKCPXL6CZ7RUBME2PDE6/events.json","paper":"https://pith.science/paper/TDWSSZPK"},"agent_actions":{"view_html":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6","download_json":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6.json","view_paper":"https://pith.science/paper/TDWSSZPK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1306.6677&json=true","fetch_graph":"https://pith.science/api/pith-number/TDWSSZPKCPXL6CZ7RUBME2PDE6/graph.json","fetch_events":"https://pith.science/api/pith-number/TDWSSZPKCPXL6CZ7RUBME2PDE6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6/action/storage_attestation","attest_author":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6/action/author_attestation","sign_citation":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6/action/citation_signature","submit_replication":"https://pith.science/pith/TDWSSZPKCPXL6CZ7RUBME2PDE6/action/replication_record"}},"created_at":"2026-05-18T02:54:28.096911+00:00","updated_at":"2026-05-18T02:54:28.096911+00:00"}