{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:IZXOQ7XVYAWFQDWR662HBBJUSR","short_pith_number":"pith:IZXOQ7XV","schema_version":"1.0","canonical_sha256":"466ee87ef5c02c580ed1f7b47085349476e1dc798440135616d4aaae033c95f8","source":{"kind":"arxiv","id":"1709.02800","version":1},"attestation_state":"computed","paper":{"title":"GOOWE: Geometrically Optimum and Online-Weighted Ensemble Classifier for Evolving Data Streams","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Fazli Can, Hamed R. Bonab","submitted_at":"2017-09-08T00:58:40Z","abstract_excerpt":"Designing adaptive classifiers for an evolving data stream is a challenging task due to the data size and its dynamically changing nature. Combining individual classifiers in an online setting, the ensemble approach, is a well-known solution. It is possible that a subset of classifiers in the ensemble outperforms others in a time-varying fashion. However, optimum weight assignment for component classifiers is a problem which is not yet fully addressed in online evolving environments. We propose a novel data stream ensemble classifier, called Geometrically Optimum and Online-Weighted Ensemble ("},"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":"1709.02800","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-09-08T00:58:40Z","cross_cats_sorted":[],"title_canon_sha256":"b2cd6df558ce814539e7d4cfe4970d571800da97e47dc1650ea715db715e97cf","abstract_canon_sha256":"53042e188085ac6a499b26bc7a8a17ccaf702a18b832f54d74dc00e49dc55a98"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:40.460043Z","signature_b64":"lBar7LwNA7m1QOFisaIPlG9jsMVfV/ooeYH1Mdp0yRl3QXpmZ/FhkPshKWuM/BRE+f95TOw1ntnkRfD712doBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"466ee87ef5c02c580ed1f7b47085349476e1dc798440135616d4aaae033c95f8","last_reissued_at":"2026-05-18T00:35:40.459344Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:40.459344Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GOOWE: Geometrically Optimum and Online-Weighted Ensemble Classifier for Evolving Data Streams","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Fazli Can, Hamed R. Bonab","submitted_at":"2017-09-08T00:58:40Z","abstract_excerpt":"Designing adaptive classifiers for an evolving data stream is a challenging task due to the data size and its dynamically changing nature. Combining individual classifiers in an online setting, the ensemble approach, is a well-known solution. It is possible that a subset of classifiers in the ensemble outperforms others in a time-varying fashion. However, optimum weight assignment for component classifiers is a problem which is not yet fully addressed in online evolving environments. We propose a novel data stream ensemble classifier, called Geometrically Optimum and Online-Weighted Ensemble ("},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.02800","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":"1709.02800","created_at":"2026-05-18T00:35:40.459477+00:00"},{"alias_kind":"arxiv_version","alias_value":"1709.02800v1","created_at":"2026-05-18T00:35:40.459477+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.02800","created_at":"2026-05-18T00:35:40.459477+00:00"},{"alias_kind":"pith_short_12","alias_value":"IZXOQ7XVYAWF","created_at":"2026-05-18T12:31:21.493067+00:00"},{"alias_kind":"pith_short_16","alias_value":"IZXOQ7XVYAWFQDWR","created_at":"2026-05-18T12:31:21.493067+00:00"},{"alias_kind":"pith_short_8","alias_value":"IZXOQ7XV","created_at":"2026-05-18T12:31:21.493067+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/IZXOQ7XVYAWFQDWR662HBBJUSR","json":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR.json","graph_json":"https://pith.science/api/pith-number/IZXOQ7XVYAWFQDWR662HBBJUSR/graph.json","events_json":"https://pith.science/api/pith-number/IZXOQ7XVYAWFQDWR662HBBJUSR/events.json","paper":"https://pith.science/paper/IZXOQ7XV"},"agent_actions":{"view_html":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR","download_json":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR.json","view_paper":"https://pith.science/paper/IZXOQ7XV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1709.02800&json=true","fetch_graph":"https://pith.science/api/pith-number/IZXOQ7XVYAWFQDWR662HBBJUSR/graph.json","fetch_events":"https://pith.science/api/pith-number/IZXOQ7XVYAWFQDWR662HBBJUSR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR/action/storage_attestation","attest_author":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR/action/author_attestation","sign_citation":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR/action/citation_signature","submit_replication":"https://pith.science/pith/IZXOQ7XVYAWFQDWR662HBBJUSR/action/replication_record"}},"created_at":"2026-05-18T00:35:40.459477+00:00","updated_at":"2026-05-18T00:35:40.459477+00:00"}