{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:4NZZC6V25QU6N4ZNUZOVAXYY7W","short_pith_number":"pith:4NZZC6V2","schema_version":"1.0","canonical_sha256":"e373917abaec29e6f32da65d505f18fda974975005bbb0733fd5992d987cea63","source":{"kind":"arxiv","id":"1604.08079","version":2},"attestation_state":"computed","paper":{"title":"UBL: an R package for Utility-based Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.MS","authors_text":"Luis Torgo, Paula Branco, Rita P. Ribeiro","submitted_at":"2016-04-27T14:13:11Z","abstract_excerpt":"This document describes the R package UBL that allows the use of several methods for handling utility-based learning problems. Classification and regression problems that assume non-uniform costs and/or benefits pose serious challenges to predictive analytic tasks. In the context of meteorology, finance, medicine, ecology, among many other, specific domain information concerning the preference bias of the users must be taken into account to enhance the models predictive performance. To deal with this problem, a large number of techniques was proposed by the research community for both classifi"},"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":"1604.08079","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MS","submitted_at":"2016-04-27T14:13:11Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"0d02d5d393f2b839794180ebd8d81ed0c66a37416e1e33be12ac380bd361a5a5","abstract_canon_sha256":"288247cc7bb25ab3738f2ef97ef8d195d4f37dacae52c226d1bbd217da6ee6d4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:08.004694Z","signature_b64":"NhwuBQVKuqAVh5pcm3eFz72AfNXrLMuvbLo98FWuuEOCOXaRAuPdVswdFTxOSbihawvCh5IpGQCObG951ERmAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e373917abaec29e6f32da65d505f18fda974975005bbb0733fd5992d987cea63","last_reissued_at":"2026-05-18T01:11:08.004142Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:08.004142Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"UBL: an R package for Utility-based Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.MS","authors_text":"Luis Torgo, Paula Branco, Rita P. Ribeiro","submitted_at":"2016-04-27T14:13:11Z","abstract_excerpt":"This document describes the R package UBL that allows the use of several methods for handling utility-based learning problems. Classification and regression problems that assume non-uniform costs and/or benefits pose serious challenges to predictive analytic tasks. In the context of meteorology, finance, medicine, ecology, among many other, specific domain information concerning the preference bias of the users must be taken into account to enhance the models predictive performance. To deal with this problem, a large number of techniques was proposed by the research community for both classifi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.08079","kind":"arxiv","version":2},"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":"1604.08079","created_at":"2026-05-18T01:11:08.004221+00:00"},{"alias_kind":"arxiv_version","alias_value":"1604.08079v2","created_at":"2026-05-18T01:11:08.004221+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.08079","created_at":"2026-05-18T01:11:08.004221+00:00"},{"alias_kind":"pith_short_12","alias_value":"4NZZC6V25QU6","created_at":"2026-05-18T12:29:58.707656+00:00"},{"alias_kind":"pith_short_16","alias_value":"4NZZC6V25QU6N4ZN","created_at":"2026-05-18T12:29:58.707656+00:00"},{"alias_kind":"pith_short_8","alias_value":"4NZZC6V2","created_at":"2026-05-18T12:29:58.707656+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/4NZZC6V25QU6N4ZNUZOVAXYY7W","json":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W.json","graph_json":"https://pith.science/api/pith-number/4NZZC6V25QU6N4ZNUZOVAXYY7W/graph.json","events_json":"https://pith.science/api/pith-number/4NZZC6V25QU6N4ZNUZOVAXYY7W/events.json","paper":"https://pith.science/paper/4NZZC6V2"},"agent_actions":{"view_html":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W","download_json":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W.json","view_paper":"https://pith.science/paper/4NZZC6V2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1604.08079&json=true","fetch_graph":"https://pith.science/api/pith-number/4NZZC6V25QU6N4ZNUZOVAXYY7W/graph.json","fetch_events":"https://pith.science/api/pith-number/4NZZC6V25QU6N4ZNUZOVAXYY7W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W/action/storage_attestation","attest_author":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W/action/author_attestation","sign_citation":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W/action/citation_signature","submit_replication":"https://pith.science/pith/4NZZC6V25QU6N4ZNUZOVAXYY7W/action/replication_record"}},"created_at":"2026-05-18T01:11:08.004221+00:00","updated_at":"2026-05-18T01:11:08.004221+00:00"}