{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:ECKAFD32PEAHHNSCKG5JOQBVSO","short_pith_number":"pith:ECKAFD32","schema_version":"1.0","canonical_sha256":"2094028f7a790073b64251ba974035938daee81bb46ef19cd5e009c7d41433bf","source":{"kind":"arxiv","id":"2009.06078","version":1},"attestation_state":"computed","paper":{"title":"Random boosting and random^2 forests -- A random tree depth injection approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.CO","stat.ME"],"primary_cat":"stat.ML","authors_text":"Andreas Groll, Carsten Jentsch, Daniel Horn, Thi Ngoc Tien Tran, Tobias Markus Krabel","submitted_at":"2020-09-13T20:14:50Z","abstract_excerpt":"The induction of additional randomness in parallel and sequential ensemble methods has proven to be worthwhile in many aspects. In this manuscript, we propose and examine a novel random tree depth injection approach suitable for sequential and parallel tree-based approaches including Boosting and Random Forests. The resulting methods are called \\emph{Random Boost} and \\emph{Random$^2$ Forest}. Both approaches serve as valuable extensions to the existing literature on the gradient boosting framework and random forests. A Monte Carlo simulation, in which tree-shaped data sets with different numb"},"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":"2009.06078","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2020-09-13T20:14:50Z","cross_cats_sorted":["cs.LG","stat.CO","stat.ME"],"title_canon_sha256":"5f7a6fdecd0e8c02f025958ad54451cd46ad311f9d7f98e2448d33d812d878be","abstract_canon_sha256":"fd534efdf8c7d4a037160e4c0a8c18d9208a1f76f1ab49d3d5e4588ab19acd51"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:35:04.461693Z","signature_b64":"zKQ+gZ0k3eUTIASMd5i+Nn/yRwQOl/tfHghrvZQERbuAS8CbFl4xCBpCSAn7bHJRrBJvoOXHU3OI2pzh4ukhAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2094028f7a790073b64251ba974035938daee81bb46ef19cd5e009c7d41433bf","last_reissued_at":"2026-07-05T01:35:04.461298Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:35:04.461298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Random boosting and random^2 forests -- A random tree depth injection approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.CO","stat.ME"],"primary_cat":"stat.ML","authors_text":"Andreas Groll, Carsten Jentsch, Daniel Horn, Thi Ngoc Tien Tran, Tobias Markus Krabel","submitted_at":"2020-09-13T20:14:50Z","abstract_excerpt":"The induction of additional randomness in parallel and sequential ensemble methods has proven to be worthwhile in many aspects. In this manuscript, we propose and examine a novel random tree depth injection approach suitable for sequential and parallel tree-based approaches including Boosting and Random Forests. The resulting methods are called \\emph{Random Boost} and \\emph{Random$^2$ Forest}. Both approaches serve as valuable extensions to the existing literature on the gradient boosting framework and random forests. A Monte Carlo simulation, in which tree-shaped data sets with different numb"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.06078","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2009.06078/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2009.06078","created_at":"2026-07-05T01:35:04.461361+00:00"},{"alias_kind":"arxiv_version","alias_value":"2009.06078v1","created_at":"2026-07-05T01:35:04.461361+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.06078","created_at":"2026-07-05T01:35:04.461361+00:00"},{"alias_kind":"pith_short_12","alias_value":"ECKAFD32PEAH","created_at":"2026-07-05T01:35:04.461361+00:00"},{"alias_kind":"pith_short_16","alias_value":"ECKAFD32PEAHHNSC","created_at":"2026-07-05T01:35:04.461361+00:00"},{"alias_kind":"pith_short_8","alias_value":"ECKAFD32","created_at":"2026-07-05T01:35:04.461361+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/ECKAFD32PEAHHNSCKG5JOQBVSO","json":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO.json","graph_json":"https://pith.science/api/pith-number/ECKAFD32PEAHHNSCKG5JOQBVSO/graph.json","events_json":"https://pith.science/api/pith-number/ECKAFD32PEAHHNSCKG5JOQBVSO/events.json","paper":"https://pith.science/paper/ECKAFD32"},"agent_actions":{"view_html":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO","download_json":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO.json","view_paper":"https://pith.science/paper/ECKAFD32","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2009.06078&json=true","fetch_graph":"https://pith.science/api/pith-number/ECKAFD32PEAHHNSCKG5JOQBVSO/graph.json","fetch_events":"https://pith.science/api/pith-number/ECKAFD32PEAHHNSCKG5JOQBVSO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO/action/storage_attestation","attest_author":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO/action/author_attestation","sign_citation":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO/action/citation_signature","submit_replication":"https://pith.science/pith/ECKAFD32PEAHHNSCKG5JOQBVSO/action/replication_record"}},"created_at":"2026-07-05T01:35:04.461361+00:00","updated_at":"2026-07-05T01:35:04.461361+00:00"}