{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:3ME6LZC2OK2PVSBME36TK7LBCU","short_pith_number":"pith:3ME6LZC2","schema_version":"1.0","canonical_sha256":"db09e5e45a72b4fac82c26fd357d61152571ae74f456bd2fd26910e2628f97cb","source":{"kind":"arxiv","id":"1303.4015","version":2},"attestation_state":"computed","paper":{"title":"On multi-class learning through the minimization of the confusion matrix norm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"C\\'ecile Capponi (LIF), Sokol Ko\\c{c}o (LIF)","submitted_at":"2013-03-16T20:09:16Z","abstract_excerpt":"In imbalanced multi-class classification problems, the misclassification rate as an error measure may not be a relevant choice. Several methods have been developed where the performance measure retained richer information than the mere misclassification rate: misclassification costs, ROC-based information, etc. Following this idea of dealing with alternate measures of performance, we propose to address imbalanced classification problems by using a new measure to be optimized: the norm of the confusion matrix. Indeed, recent results show that using the norm of the confusion matrix as an error m"},"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":"1303.4015","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2013-03-16T20:09:16Z","cross_cats_sorted":[],"title_canon_sha256":"bb2efb8a80c2c8a577dcdd8c0fe007c498dc57c4efdb31dafa041d411e6e71bc","abstract_canon_sha256":"e0d6ada2cc87146b33323def78762654094cd02c34a4d9e06a4c0dc3fbaeaa2f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:08:14.158468Z","signature_b64":"RkQbFolCQqfRnoy+gSnAw1xUfU5FXrRO5ZV+LjcfbhNcqxzfMS71fI4s6STRYk9FqZqJQWyqT047PUfBYp5qCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db09e5e45a72b4fac82c26fd357d61152571ae74f456bd2fd26910e2628f97cb","last_reissued_at":"2026-05-18T03:08:14.157740Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:08:14.157740Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"On multi-class learning through the minimization of the confusion matrix norm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"C\\'ecile Capponi (LIF), Sokol Ko\\c{c}o (LIF)","submitted_at":"2013-03-16T20:09:16Z","abstract_excerpt":"In imbalanced multi-class classification problems, the misclassification rate as an error measure may not be a relevant choice. Several methods have been developed where the performance measure retained richer information than the mere misclassification rate: misclassification costs, ROC-based information, etc. Following this idea of dealing with alternate measures of performance, we propose to address imbalanced classification problems by using a new measure to be optimized: the norm of the confusion matrix. Indeed, recent results show that using the norm of the confusion matrix as an error m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1303.4015","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":"1303.4015","created_at":"2026-05-18T03:08:14.157854+00:00"},{"alias_kind":"arxiv_version","alias_value":"1303.4015v2","created_at":"2026-05-18T03:08:14.157854+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1303.4015","created_at":"2026-05-18T03:08:14.157854+00:00"},{"alias_kind":"pith_short_12","alias_value":"3ME6LZC2OK2P","created_at":"2026-05-18T12:27:32.513160+00:00"},{"alias_kind":"pith_short_16","alias_value":"3ME6LZC2OK2PVSBM","created_at":"2026-05-18T12:27:32.513160+00:00"},{"alias_kind":"pith_short_8","alias_value":"3ME6LZC2","created_at":"2026-05-18T12:27:32.513160+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/3ME6LZC2OK2PVSBME36TK7LBCU","json":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU.json","graph_json":"https://pith.science/api/pith-number/3ME6LZC2OK2PVSBME36TK7LBCU/graph.json","events_json":"https://pith.science/api/pith-number/3ME6LZC2OK2PVSBME36TK7LBCU/events.json","paper":"https://pith.science/paper/3ME6LZC2"},"agent_actions":{"view_html":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU","download_json":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU.json","view_paper":"https://pith.science/paper/3ME6LZC2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1303.4015&json=true","fetch_graph":"https://pith.science/api/pith-number/3ME6LZC2OK2PVSBME36TK7LBCU/graph.json","fetch_events":"https://pith.science/api/pith-number/3ME6LZC2OK2PVSBME36TK7LBCU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU/action/storage_attestation","attest_author":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU/action/author_attestation","sign_citation":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU/action/citation_signature","submit_replication":"https://pith.science/pith/3ME6LZC2OK2PVSBME36TK7LBCU/action/replication_record"}},"created_at":"2026-05-18T03:08:14.157854+00:00","updated_at":"2026-05-18T03:08:14.157854+00:00"}