{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:32YKIVFYEOL364RGO5PTPBLOZU","short_pith_number":"pith:32YKIVFY","schema_version":"1.0","canonical_sha256":"deb0a454b82397bf7226775f37856ecd36ca91dcdf328bedca8260df60d94a9f","source":{"kind":"arxiv","id":"1710.09515","version":1},"attestation_state":"computed","paper":{"title":"Soft Methodology for Cost-and-error Sensitive Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chi-Hung Lin, Da-Wei Wang, Hsuan-Tien Lin, Te-Kang Jan","submitted_at":"2017-10-26T02:39:29Z","abstract_excerpt":"Many real-world data mining applications need varying cost for different types of classification errors and thus call for cost-sensitive classification algorithms. Existing algorithms for cost-sensitive classification are successful in terms of minimizing the cost, but can result in a high error rate as the trade-off. The high error rate holds back the practical use of those algorithms. In this paper, we propose a novel cost-sensitive classification methodology that takes both the cost and the error rate into account. The methodology, called soft cost-sensitive classification, is established f"},"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":"1710.09515","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-10-26T02:39:29Z","cross_cats_sorted":[],"title_canon_sha256":"d01e676fda51a1695858fee7906c124f27941b5c38ec7155d650fa8d4e576fc7","abstract_canon_sha256":"0963c3aad1acdcf4b1725a684cb792a47146e1ef2f7f5305c461873d2bb48c1b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:59.220530Z","signature_b64":"gLSGus1ODks7aiaXM6qb2Sfs6oiflRjMqxSEVdr9NDtTwdZ5dwuZBCVizxzlpDXSWjOwQR/quJj+pv5q8TKTCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"deb0a454b82397bf7226775f37856ecd36ca91dcdf328bedca8260df60d94a9f","last_reissued_at":"2026-05-18T00:31:59.220046Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:59.220046Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Soft Methodology for Cost-and-error Sensitive Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chi-Hung Lin, Da-Wei Wang, Hsuan-Tien Lin, Te-Kang Jan","submitted_at":"2017-10-26T02:39:29Z","abstract_excerpt":"Many real-world data mining applications need varying cost for different types of classification errors and thus call for cost-sensitive classification algorithms. Existing algorithms for cost-sensitive classification are successful in terms of minimizing the cost, but can result in a high error rate as the trade-off. The high error rate holds back the practical use of those algorithms. In this paper, we propose a novel cost-sensitive classification methodology that takes both the cost and the error rate into account. The methodology, called soft cost-sensitive classification, is established f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.09515","kind":"arxiv","version":1},"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":"1710.09515","created_at":"2026-05-18T00:31:59.220113+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.09515v1","created_at":"2026-05-18T00:31:59.220113+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.09515","created_at":"2026-05-18T00:31:59.220113+00:00"},{"alias_kind":"pith_short_12","alias_value":"32YKIVFYEOL3","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_16","alias_value":"32YKIVFYEOL364RG","created_at":"2026-05-18T12:30:55.937587+00:00"},{"alias_kind":"pith_short_8","alias_value":"32YKIVFY","created_at":"2026-05-18T12:30:55.937587+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/32YKIVFYEOL364RGO5PTPBLOZU","json":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU.json","graph_json":"https://pith.science/api/pith-number/32YKIVFYEOL364RGO5PTPBLOZU/graph.json","events_json":"https://pith.science/api/pith-number/32YKIVFYEOL364RGO5PTPBLOZU/events.json","paper":"https://pith.science/paper/32YKIVFY"},"agent_actions":{"view_html":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU","download_json":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU.json","view_paper":"https://pith.science/paper/32YKIVFY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.09515&json=true","fetch_graph":"https://pith.science/api/pith-number/32YKIVFYEOL364RGO5PTPBLOZU/graph.json","fetch_events":"https://pith.science/api/pith-number/32YKIVFYEOL364RGO5PTPBLOZU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU/action/storage_attestation","attest_author":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU/action/author_attestation","sign_citation":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU/action/citation_signature","submit_replication":"https://pith.science/pith/32YKIVFYEOL364RGO5PTPBLOZU/action/replication_record"}},"created_at":"2026-05-18T00:31:59.220113+00:00","updated_at":"2026-05-18T00:31:59.220113+00:00"}