{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:RL47ADBBLG6QQ7IIKE2ZEGZYCB","short_pith_number":"pith:RL47ADBB","schema_version":"1.0","canonical_sha256":"8af9f00c2159bd087d085135921b38105782b278df4540fd1445ab6eac4c429e","source":{"kind":"arxiv","id":"1304.3779","version":1},"attestation_state":"computed","paper":{"title":"Improving Generalization Ability of Genetic Programming: Comparative Study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Tejashvi R. Naik, Vipul K. Dabhi","submitted_at":"2013-04-13T05:16:54Z","abstract_excerpt":"In the field of empirical modeling using Genetic Programming (GP), it is important to evolve solution with good generalization ability. Generalization ability of GP solutions get affected by two important issues: bloat and over-fitting. Bloat is uncontrolled growth of code without any gain in fitness and important issue in GP. We surveyed and classified existing literature related to different techniques used by GP research community to deal with the issue of bloat. Moreover, the classifications of different bloat control approaches and measures for bloat are discussed. Next, we tested four bl"},"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":"1304.3779","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2013-04-13T05:16:54Z","cross_cats_sorted":[],"title_canon_sha256":"4cdd791beb63d2dabe01925505a0b124dc085a76a6e7014838367dda48034505","abstract_canon_sha256":"22d1306c57a00908b97f2b4d35b0f3cbe8c32b7dc1bc4eec981fb7ddd24d8fa6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:28:04.370673Z","signature_b64":"dsPC97PvARLLJFsDFq5VWkjp6ghNLwK30E1gWhEFLqHab3iILFfCKNuCXD3TAqas2FJl875nWrNKl0LSpPHuCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8af9f00c2159bd087d085135921b38105782b278df4540fd1445ab6eac4c429e","last_reissued_at":"2026-05-18T03:28:04.369906Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:28:04.369906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Improving Generalization Ability of Genetic Programming: Comparative Study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Tejashvi R. Naik, Vipul K. Dabhi","submitted_at":"2013-04-13T05:16:54Z","abstract_excerpt":"In the field of empirical modeling using Genetic Programming (GP), it is important to evolve solution with good generalization ability. Generalization ability of GP solutions get affected by two important issues: bloat and over-fitting. Bloat is uncontrolled growth of code without any gain in fitness and important issue in GP. We surveyed and classified existing literature related to different techniques used by GP research community to deal with the issue of bloat. Moreover, the classifications of different bloat control approaches and measures for bloat are discussed. Next, we tested four bl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1304.3779","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":"1304.3779","created_at":"2026-05-18T03:28:04.370005+00:00"},{"alias_kind":"arxiv_version","alias_value":"1304.3779v1","created_at":"2026-05-18T03:28:04.370005+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1304.3779","created_at":"2026-05-18T03:28:04.370005+00:00"},{"alias_kind":"pith_short_12","alias_value":"RL47ADBBLG6Q","created_at":"2026-05-18T12:27:57.521954+00:00"},{"alias_kind":"pith_short_16","alias_value":"RL47ADBBLG6QQ7II","created_at":"2026-05-18T12:27:57.521954+00:00"},{"alias_kind":"pith_short_8","alias_value":"RL47ADBB","created_at":"2026-05-18T12:27:57.521954+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/RL47ADBBLG6QQ7IIKE2ZEGZYCB","json":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB.json","graph_json":"https://pith.science/api/pith-number/RL47ADBBLG6QQ7IIKE2ZEGZYCB/graph.json","events_json":"https://pith.science/api/pith-number/RL47ADBBLG6QQ7IIKE2ZEGZYCB/events.json","paper":"https://pith.science/paper/RL47ADBB"},"agent_actions":{"view_html":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB","download_json":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB.json","view_paper":"https://pith.science/paper/RL47ADBB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1304.3779&json=true","fetch_graph":"https://pith.science/api/pith-number/RL47ADBBLG6QQ7IIKE2ZEGZYCB/graph.json","fetch_events":"https://pith.science/api/pith-number/RL47ADBBLG6QQ7IIKE2ZEGZYCB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB/action/storage_attestation","attest_author":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB/action/author_attestation","sign_citation":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB/action/citation_signature","submit_replication":"https://pith.science/pith/RL47ADBBLG6QQ7IIKE2ZEGZYCB/action/replication_record"}},"created_at":"2026-05-18T03:28:04.370005+00:00","updated_at":"2026-05-18T03:28:04.370005+00:00"}