{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:EWSENS7BNRYYNBSSLVUUXX557F","short_pith_number":"pith:EWSENS7B","canonical_record":{"source":{"id":"1603.06212","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-03-20T13:32:27Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"468dadbf792eeaf2790b86a3f6346ae75e7d53b0a35fed1e85af9aea298a8fa7","abstract_canon_sha256":"aebc428039b02ceea3bd85692f8501de3188503cc7d4da1a8a79dd226b027c21"},"schema_version":"1.0"},"canonical_sha256":"25a446cbe16c718686525d694bdfbdf948ca214add4ee9465950eb72715d4dbd","source":{"kind":"arxiv","id":"1603.06212","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1603.06212","created_at":"2026-05-18T01:18:50Z"},{"alias_kind":"arxiv_version","alias_value":"1603.06212v1","created_at":"2026-05-18T01:18:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.06212","created_at":"2026-05-18T01:18:50Z"},{"alias_kind":"pith_short_12","alias_value":"EWSENS7BNRYY","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"EWSENS7BNRYYNBSS","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"EWSENS7B","created_at":"2026-05-18T12:30:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:EWSENS7BNRYYNBSSLVUUXX557F","target":"record","payload":{"canonical_record":{"source":{"id":"1603.06212","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-03-20T13:32:27Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"468dadbf792eeaf2790b86a3f6346ae75e7d53b0a35fed1e85af9aea298a8fa7","abstract_canon_sha256":"aebc428039b02ceea3bd85692f8501de3188503cc7d4da1a8a79dd226b027c21"},"schema_version":"1.0"},"canonical_sha256":"25a446cbe16c718686525d694bdfbdf948ca214add4ee9465950eb72715d4dbd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:18:50.019998Z","signature_b64":"w9lqfFTQez695Z7nlt4fldBFB4qap9Rr8cfdtvi15GF+i7ibbXhNOXuwh+e62hpa4hrTnxIwwDVEbCooPsofCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"25a446cbe16c718686525d694bdfbdf948ca214add4ee9465950eb72715d4dbd","last_reissued_at":"2026-05-18T01:18:50.019442Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:18:50.019442Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1603.06212","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:18:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"igB5LnFhnwKBu9lFPLh8/iJZd1NELj9TsD3yXlm2ajgWS7jNn6e9gMSh49oj2x75dWekoGup/V9s7bxKa46xAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T00:59:11.232855Z"},"content_sha256":"6d2f08a8ddfba9785ff2b898f4bed1abba0610465bfb7c41a4f10c79e599f261","schema_version":"1.0","event_id":"sha256:6d2f08a8ddfba9785ff2b898f4bed1abba0610465bfb7c41a4f10c79e599f261"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:EWSENS7BNRYYNBSSLVUUXX557F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.NE","authors_text":"Jason H. Moore, Nathan Bartley, Randal S. Olson, Ryan J. Urbanowicz","submitted_at":"2016-03-20T13:32:27Z","abstract_excerpt":"As the field of data science continues to grow, there will be an ever-increasing demand for tools that make machine learning accessible to non-experts. In this paper, we introduce the concept of tree-based pipeline optimization for automating one of the most tedious parts of machine learning---pipeline design. We implement an open source Tree-based Pipeline Optimization Tool (TPOT) in Python and demonstrate its effectiveness on a series of simulated and real-world benchmark data sets. In particular, we show that TPOT can design machine learning pipelines that provide a significant improvement "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.06212","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:18:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ckw50yujiqofOfwfTzhkrpbclbNjzuYNkpXytyhzVedXMm2kUXEEUWccSrXpbAoaqv5i5l2SzW7Kda3hpxLlDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T00:59:11.233202Z"},"content_sha256":"4040937dcdc31b318f28ba49f5f476240d8c44ae9a8325e9976199ebe99c4882","schema_version":"1.0","event_id":"sha256:4040937dcdc31b318f28ba49f5f476240d8c44ae9a8325e9976199ebe99c4882"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EWSENS7BNRYYNBSSLVUUXX557F/bundle.json","state_url":"https://pith.science/pith/EWSENS7BNRYYNBSSLVUUXX557F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EWSENS7BNRYYNBSSLVUUXX557F/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":"2026-06-22T00:59:11Z","links":{"resolver":"https://pith.science/pith/EWSENS7BNRYYNBSSLVUUXX557F","bundle":"https://pith.science/pith/EWSENS7BNRYYNBSSLVUUXX557F/bundle.json","state":"https://pith.science/pith/EWSENS7BNRYYNBSSLVUUXX557F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EWSENS7BNRYYNBSSLVUUXX557F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:EWSENS7BNRYYNBSSLVUUXX557F","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":"aebc428039b02ceea3bd85692f8501de3188503cc7d4da1a8a79dd226b027c21","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-03-20T13:32:27Z","title_canon_sha256":"468dadbf792eeaf2790b86a3f6346ae75e7d53b0a35fed1e85af9aea298a8fa7"},"schema_version":"1.0","source":{"id":"1603.06212","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1603.06212","created_at":"2026-05-18T01:18:50Z"},{"alias_kind":"arxiv_version","alias_value":"1603.06212v1","created_at":"2026-05-18T01:18:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.06212","created_at":"2026-05-18T01:18:50Z"},{"alias_kind":"pith_short_12","alias_value":"EWSENS7BNRYY","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"EWSENS7BNRYYNBSS","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"EWSENS7B","created_at":"2026-05-18T12:30:15Z"}],"graph_snapshots":[{"event_id":"sha256:4040937dcdc31b318f28ba49f5f476240d8c44ae9a8325e9976199ebe99c4882","target":"graph","created_at":"2026-05-18T01:18:50Z","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"},"paper":{"abstract_excerpt":"As the field of data science continues to grow, there will be an ever-increasing demand for tools that make machine learning accessible to non-experts. In this paper, we introduce the concept of tree-based pipeline optimization for automating one of the most tedious parts of machine learning---pipeline design. We implement an open source Tree-based Pipeline Optimization Tool (TPOT) in Python and demonstrate its effectiveness on a series of simulated and real-world benchmark data sets. In particular, we show that TPOT can design machine learning pipelines that provide a significant improvement ","authors_text":"Jason H. Moore, Nathan Bartley, Randal S. Olson, Ryan J. Urbanowicz","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-03-20T13:32:27Z","title":"Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.06212","kind":"arxiv","version":1},"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":"sha256:6d2f08a8ddfba9785ff2b898f4bed1abba0610465bfb7c41a4f10c79e599f261","target":"record","created_at":"2026-05-18T01:18:50Z","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":"aebc428039b02ceea3bd85692f8501de3188503cc7d4da1a8a79dd226b027c21","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2016-03-20T13:32:27Z","title_canon_sha256":"468dadbf792eeaf2790b86a3f6346ae75e7d53b0a35fed1e85af9aea298a8fa7"},"schema_version":"1.0","source":{"id":"1603.06212","kind":"arxiv","version":1}},"canonical_sha256":"25a446cbe16c718686525d694bdfbdf948ca214add4ee9465950eb72715d4dbd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"25a446cbe16c718686525d694bdfbdf948ca214add4ee9465950eb72715d4dbd","first_computed_at":"2026-05-18T01:18:50.019442Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:18:50.019442Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"w9lqfFTQez695Z7nlt4fldBFB4qap9Rr8cfdtvi15GF+i7ibbXhNOXuwh+e62hpa4hrTnxIwwDVEbCooPsofCw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:18:50.019998Z","signed_message":"canonical_sha256_bytes"},"source_id":"1603.06212","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6d2f08a8ddfba9785ff2b898f4bed1abba0610465bfb7c41a4f10c79e599f261","sha256:4040937dcdc31b318f28ba49f5f476240d8c44ae9a8325e9976199ebe99c4882"],"state_sha256":"78535cf3391596440987412f3b3ee9ddc642376e0862187b1c3d350856034f2e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eQhJtjgf89DKnp460ThRD8bJy08cnz3V++2Y1ymj72xKtUQY0VWw3l+7ayOzZuYNZVpWtFUCwePaKXOoTeh/DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T00:59:11.235525Z","bundle_sha256":"3481fc4713be07ed6c2101f029e5435d0c9222509d9328ff9993cfaffc4f63c7"}}