{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:VND26BFQ6J2GFB3BEN6FDYVBVA","short_pith_number":"pith:VND26BFQ","schema_version":"1.0","canonical_sha256":"ab47af04b0f274628761237c51e2a1a8291adf7f593a967ed738c758a66bfcea","source":{"kind":"arxiv","id":"1609.09471","version":2},"attestation_state":"computed","paper":{"title":"Classifier comparison using precision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Lovedeep Gondara","submitted_at":"2016-09-29T19:19:29Z","abstract_excerpt":"New proposed models are often compared to state-of-the-art using statistical significance testing. Literature is scarce for classifier comparison using metrics other than accuracy. We present a survey of statistical methods that can be used for classifier comparison using precision, accounting for inter-precision correlation arising from use of same dataset. Comparisons are made using per-class precision and methods presented to test global null hypothesis of an overall model comparison. Comparisons are extended to multiple multi-class classifiers and to models using cross validation or its va"},"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":"1609.09471","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-09-29T19:19:29Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"feb16b0639d24f4993d43e3fb8747d7fc1692534181632a87dbe25a5fdcba6a4","abstract_canon_sha256":"c84e8c5c85d92ed03ee9bfebc151cf1bf021503fb886eb86a54d1d890173c5c5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:58:28.328124Z","signature_b64":"qogJrCPIuWmrrcn9CBhsQKoqHabZbIOErncLcT33C2QYwEQ8D0vJZmGJlRqoV1uqj1lZ3YfbnF6ZwzaOsfXUDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ab47af04b0f274628761237c51e2a1a8291adf7f593a967ed738c758a66bfcea","last_reissued_at":"2026-05-18T00:58:28.327552Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:58:28.327552Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Classifier comparison using precision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Lovedeep Gondara","submitted_at":"2016-09-29T19:19:29Z","abstract_excerpt":"New proposed models are often compared to state-of-the-art using statistical significance testing. Literature is scarce for classifier comparison using metrics other than accuracy. We present a survey of statistical methods that can be used for classifier comparison using precision, accounting for inter-precision correlation arising from use of same dataset. Comparisons are made using per-class precision and methods presented to test global null hypothesis of an overall model comparison. Comparisons are extended to multiple multi-class classifiers and to models using cross validation or its va"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.09471","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":"1609.09471","created_at":"2026-05-18T00:58:28.327636+00:00"},{"alias_kind":"arxiv_version","alias_value":"1609.09471v2","created_at":"2026-05-18T00:58:28.327636+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.09471","created_at":"2026-05-18T00:58:28.327636+00:00"},{"alias_kind":"pith_short_12","alias_value":"VND26BFQ6J2G","created_at":"2026-05-18T12:30:48.956258+00:00"},{"alias_kind":"pith_short_16","alias_value":"VND26BFQ6J2GFB3B","created_at":"2026-05-18T12:30:48.956258+00:00"},{"alias_kind":"pith_short_8","alias_value":"VND26BFQ","created_at":"2026-05-18T12:30:48.956258+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/VND26BFQ6J2GFB3BEN6FDYVBVA","json":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA.json","graph_json":"https://pith.science/api/pith-number/VND26BFQ6J2GFB3BEN6FDYVBVA/graph.json","events_json":"https://pith.science/api/pith-number/VND26BFQ6J2GFB3BEN6FDYVBVA/events.json","paper":"https://pith.science/paper/VND26BFQ"},"agent_actions":{"view_html":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA","download_json":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA.json","view_paper":"https://pith.science/paper/VND26BFQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1609.09471&json=true","fetch_graph":"https://pith.science/api/pith-number/VND26BFQ6J2GFB3BEN6FDYVBVA/graph.json","fetch_events":"https://pith.science/api/pith-number/VND26BFQ6J2GFB3BEN6FDYVBVA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA/action/storage_attestation","attest_author":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA/action/author_attestation","sign_citation":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA/action/citation_signature","submit_replication":"https://pith.science/pith/VND26BFQ6J2GFB3BEN6FDYVBVA/action/replication_record"}},"created_at":"2026-05-18T00:58:28.327636+00:00","updated_at":"2026-05-18T00:58:28.327636+00:00"}