{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:EBB54Y4RORMO63VOOXE6LH62VU","short_pith_number":"pith:EBB54Y4R","canonical_record":{"source":{"id":"2504.16268","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T21:03:31Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"391ca3b4af3318c63d9a100bbffc35ab6e165fcfe633e024d4b0692951a27fa5","abstract_canon_sha256":"29651d2981a993fcbffac1facf22a44f0d87ed3f8791c87a813599b4995b8b2e"},"schema_version":"1.0"},"canonical_sha256":"2043de63917458ef6eae75c9e59fdaad281e9ed2af8d2b5b4a088527d02d0344","source":{"kind":"arxiv","id":"2504.16268","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.16268","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"arxiv_version","alias_value":"2504.16268v2","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16268","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_12","alias_value":"EBB54Y4RORMO","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_16","alias_value":"EBB54Y4RORMO63VO","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_8","alias_value":"EBB54Y4R","created_at":"2026-07-05T10:53:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:EBB54Y4RORMO63VOOXE6LH62VU","target":"record","payload":{"canonical_record":{"source":{"id":"2504.16268","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T21:03:31Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"391ca3b4af3318c63d9a100bbffc35ab6e165fcfe633e024d4b0692951a27fa5","abstract_canon_sha256":"29651d2981a993fcbffac1facf22a44f0d87ed3f8791c87a813599b4995b8b2e"},"schema_version":"1.0"},"canonical_sha256":"2043de63917458ef6eae75c9e59fdaad281e9ed2af8d2b5b4a088527d02d0344","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:53:54.853306Z","signature_b64":"q/AOdiQ4RKObbMr+WmrpFXkFSPvvZhoFFMbcCFKMYNadXlpJmXGrM4jwNuhW9Qs09mmpLPbWNuIRi2bX/yP9CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2043de63917458ef6eae75c9e59fdaad281e9ed2af8d2b5b4a088527d02d0344","last_reissued_at":"2026-07-05T10:53:54.852754Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:53:54.852754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.16268","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:53:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YS+4nxj32jFEJYQewGc5xGVQdwDR3/TCHRQT+76PBhCEQ+xUpTYu61qrSMGJ8OR3W+iW6hn+n8P4KnDDY4RZCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T23:40:09.181569Z"},"content_sha256":"1231ad57ed5186cd3a1b95c656a8035509719502ffa866f63b4e7095b7c91782","schema_version":"1.0","event_id":"sha256:1231ad57ed5186cd3a1b95c656a8035509719502ffa866f63b4e7095b7c91782"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:EBB54Y4RORMO63VOOXE6LH62VU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Boosting KNNClassifier Performance with Opposition-Based Data Transformation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Abdesslem Layeb","submitted_at":"2025-04-22T21:03:31Z","abstract_excerpt":"In this paper, we introduce a novel data transformation framework based on Opposition-Based Learning (OBL) to boost the performance of traditional classification algorithms. Originally developed to accelerate convergence in optimization tasks, OBL is leveraged here to generate synthetic opposite samples that enrich the training data and improve decision boundary formation. We explore three OBL variants Global OBL, Class-Wise OBL, and Localized Class-Wise OBL and integrate them with K-Nearest Neighbors (KNN). Extensive experiments conducted on 26 heterogeneous and high-dimensional datasets demo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16268","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2504.16268/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:53:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BQEKUdpdwJGuVMKnpGbMGaj2Eg4M2zfXSzlOS5KDRzM5rX3JeLh/OY9zMpH9NvLWTFoC+hzeouDgtJKehIMWBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T23:40:09.182303Z"},"content_sha256":"7e83b8abfbd492643d46469766b0376e4dd78cd83f51ff501a62064623e7abb9","schema_version":"1.0","event_id":"sha256:7e83b8abfbd492643d46469766b0376e4dd78cd83f51ff501a62064623e7abb9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EBB54Y4RORMO63VOOXE6LH62VU/bundle.json","state_url":"https://pith.science/pith/EBB54Y4RORMO63VOOXE6LH62VU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EBB54Y4RORMO63VOOXE6LH62VU/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-23T23:40:09Z","links":{"resolver":"https://pith.science/pith/EBB54Y4RORMO63VOOXE6LH62VU","bundle":"https://pith.science/pith/EBB54Y4RORMO63VOOXE6LH62VU/bundle.json","state":"https://pith.science/pith/EBB54Y4RORMO63VOOXE6LH62VU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EBB54Y4RORMO63VOOXE6LH62VU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EBB54Y4RORMO63VOOXE6LH62VU","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"29651d2981a993fcbffac1facf22a44f0d87ed3f8791c87a813599b4995b8b2e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T21:03:31Z","title_canon_sha256":"391ca3b4af3318c63d9a100bbffc35ab6e165fcfe633e024d4b0692951a27fa5"},"schema_version":"1.0","source":{"id":"2504.16268","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.16268","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"arxiv_version","alias_value":"2504.16268v2","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16268","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_12","alias_value":"EBB54Y4RORMO","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_16","alias_value":"EBB54Y4RORMO63VO","created_at":"2026-07-05T10:53:54Z"},{"alias_kind":"pith_short_8","alias_value":"EBB54Y4R","created_at":"2026-07-05T10:53:54Z"}],"graph_snapshots":[{"event_id":"sha256:7e83b8abfbd492643d46469766b0376e4dd78cd83f51ff501a62064623e7abb9","target":"graph","created_at":"2026-07-05T10:53:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2504.16268/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we introduce a novel data transformation framework based on Opposition-Based Learning (OBL) to boost the performance of traditional classification algorithms. Originally developed to accelerate convergence in optimization tasks, OBL is leveraged here to generate synthetic opposite samples that enrich the training data and improve decision boundary formation. We explore three OBL variants Global OBL, Class-Wise OBL, and Localized Class-Wise OBL and integrate them with K-Nearest Neighbors (KNN). Extensive experiments conducted on 26 heterogeneous and high-dimensional datasets demo","authors_text":"Abdesslem Layeb","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T21:03:31Z","title":"Boosting KNNClassifier Performance with Opposition-Based Data Transformation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16268","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1231ad57ed5186cd3a1b95c656a8035509719502ffa866f63b4e7095b7c91782","target":"record","created_at":"2026-07-05T10:53:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"29651d2981a993fcbffac1facf22a44f0d87ed3f8791c87a813599b4995b8b2e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-22T21:03:31Z","title_canon_sha256":"391ca3b4af3318c63d9a100bbffc35ab6e165fcfe633e024d4b0692951a27fa5"},"schema_version":"1.0","source":{"id":"2504.16268","kind":"arxiv","version":2}},"canonical_sha256":"2043de63917458ef6eae75c9e59fdaad281e9ed2af8d2b5b4a088527d02d0344","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2043de63917458ef6eae75c9e59fdaad281e9ed2af8d2b5b4a088527d02d0344","first_computed_at":"2026-07-05T10:53:54.852754Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:53:54.852754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q/AOdiQ4RKObbMr+WmrpFXkFSPvvZhoFFMbcCFKMYNadXlpJmXGrM4jwNuhW9Qs09mmpLPbWNuIRi2bX/yP9CA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:53:54.853306Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.16268","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1231ad57ed5186cd3a1b95c656a8035509719502ffa866f63b4e7095b7c91782","sha256:7e83b8abfbd492643d46469766b0376e4dd78cd83f51ff501a62064623e7abb9"],"state_sha256":"3ef718215428d3cd226dd1ffae219595192a97f97b76ffe22d68b4f0b2e32c53"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"meps+7yD3AB8nq3H+Z7vhRqMLMK4gcCmbHFl2N7KNc3ZMky6VC/BCuhNKescchKDQQ096CNyAKRN8i9F1kWrBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T23:40:09.188836Z","bundle_sha256":"73c164d710251c2cb1958457dac95d4df543e13698377d00784ca51b6908c9e7"}}