{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:S6ET4K3OPNU7DFN5ZJYIDXTSEG","short_pith_number":"pith:S6ET4K3O","canonical_record":{"source":{"id":"1703.06777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-20T14:42:27Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"497415435e047ee05c95de0e7a0db3f09a1ff47444c773947c6422184b1b445c","abstract_canon_sha256":"ee7e383a931f57a82b633a278b19a5096eadd3b609284285c7c2b0ab528662c3"},"schema_version":"1.0"},"canonical_sha256":"97893e2b6e7b69f195bdca7081de7221b309ac1206eb80d7c24415d3f0c29f1c","source":{"kind":"arxiv","id":"1703.06777","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.06777","created_at":"2026-05-18T00:48:21Z"},{"alias_kind":"arxiv_version","alias_value":"1703.06777v1","created_at":"2026-05-18T00:48:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.06777","created_at":"2026-05-18T00:48:21Z"},{"alias_kind":"pith_short_12","alias_value":"S6ET4K3OPNU7","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"S6ET4K3OPNU7DFN5","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"S6ET4K3O","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:S6ET4K3OPNU7DFN5ZJYIDXTSEG","target":"record","payload":{"canonical_record":{"source":{"id":"1703.06777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-20T14:42:27Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"497415435e047ee05c95de0e7a0db3f09a1ff47444c773947c6422184b1b445c","abstract_canon_sha256":"ee7e383a931f57a82b633a278b19a5096eadd3b609284285c7c2b0ab528662c3"},"schema_version":"1.0"},"canonical_sha256":"97893e2b6e7b69f195bdca7081de7221b309ac1206eb80d7c24415d3f0c29f1c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:48:21.772608Z","signature_b64":"mdvdV0N6fy1IiyKHWsyiBjc4yTb0XdWhCizNn2dOXJN7OfjsZ62n090fsVgVKLDILlDgTq58wBlOGzsV8rJcDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"97893e2b6e7b69f195bdca7081de7221b309ac1206eb80d7c24415d3f0c29f1c","last_reissued_at":"2026-05-18T00:48:21.771803Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:48:21.771803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.06777","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":"2026-05-18T00:48:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nL2pnQMv9FOmydn+mP1ei7OdiVtetuP9ENk/G3CjrrEIH2Lw+qOgSohK0f5U2sGa4rX3UjztX/AIF5vZjdXQBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T21:05:59.695446Z"},"content_sha256":"80b5f8a969776e0562e41ebc123469bcfd9f4dfdb168d076a6b322baa53d80d9","schema_version":"1.0","event_id":"sha256:80b5f8a969776e0562e41ebc123469bcfd9f4dfdb168d076a6b322baa53d80d9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:S6ET4K3OPNU7DFN5ZJYIDXTSEG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Anthony Bagnall, Gavin C. Cawley","submitted_at":"2017-03-20T14:42:27Z","abstract_excerpt":"We demonstrate that, for a range of state-of-the-art machine learning algorithms, the differences in generalisation performance obtained using default parameter settings and using parameters tuned via cross-validation can be similar in magnitude to the differences in performance observed between state-of-the-art and uncompetitive learning systems. This means that fair and rigorous evaluation of new learning algorithms requires performance comparison against benchmark methods with best-practice model selection procedures, rather than using default parameter settings. We investigate the sensitiv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.06777","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":"2026-05-18T00:48:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jTEmr6ZSxHmBSQFKMK1t51O/PQrcRShaxxvxqFUDjRV12VVvOY3zO1LOxbS/LS/hJVMgKB97lINhXiald5+tCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T21:05:59.695803Z"},"content_sha256":"3939e083a67e9800f3d46db0fac124e43e5fcf5fd8a128e9438ab7c2e186183a","schema_version":"1.0","event_id":"sha256:3939e083a67e9800f3d46db0fac124e43e5fcf5fd8a128e9438ab7c2e186183a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S6ET4K3OPNU7DFN5ZJYIDXTSEG/bundle.json","state_url":"https://pith.science/pith/S6ET4K3OPNU7DFN5ZJYIDXTSEG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S6ET4K3OPNU7DFN5ZJYIDXTSEG/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":"2026-06-02T21:05:59Z","links":{"resolver":"https://pith.science/pith/S6ET4K3OPNU7DFN5ZJYIDXTSEG","bundle":"https://pith.science/pith/S6ET4K3OPNU7DFN5ZJYIDXTSEG/bundle.json","state":"https://pith.science/pith/S6ET4K3OPNU7DFN5ZJYIDXTSEG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S6ET4K3OPNU7DFN5ZJYIDXTSEG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:S6ET4K3OPNU7DFN5ZJYIDXTSEG","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":"ee7e383a931f57a82b633a278b19a5096eadd3b609284285c7c2b0ab528662c3","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-20T14:42:27Z","title_canon_sha256":"497415435e047ee05c95de0e7a0db3f09a1ff47444c773947c6422184b1b445c"},"schema_version":"1.0","source":{"id":"1703.06777","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.06777","created_at":"2026-05-18T00:48:21Z"},{"alias_kind":"arxiv_version","alias_value":"1703.06777v1","created_at":"2026-05-18T00:48:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.06777","created_at":"2026-05-18T00:48:21Z"},{"alias_kind":"pith_short_12","alias_value":"S6ET4K3OPNU7","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"S6ET4K3OPNU7DFN5","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"S6ET4K3O","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:3939e083a67e9800f3d46db0fac124e43e5fcf5fd8a128e9438ab7c2e186183a","target":"graph","created_at":"2026-05-18T00:48:21Z","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":"We demonstrate that, for a range of state-of-the-art machine learning algorithms, the differences in generalisation performance obtained using default parameter settings and using parameters tuned via cross-validation can be similar in magnitude to the differences in performance observed between state-of-the-art and uncompetitive learning systems. This means that fair and rigorous evaluation of new learning algorithms requires performance comparison against benchmark methods with best-practice model selection procedures, rather than using default parameter settings. We investigate the sensitiv","authors_text":"Anthony Bagnall, Gavin C. Cawley","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-20T14:42:27Z","title":"On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.06777","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":"sha256:80b5f8a969776e0562e41ebc123469bcfd9f4dfdb168d076a6b322baa53d80d9","target":"record","created_at":"2026-05-18T00:48:21Z","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":"ee7e383a931f57a82b633a278b19a5096eadd3b609284285c7c2b0ab528662c3","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-03-20T14:42:27Z","title_canon_sha256":"497415435e047ee05c95de0e7a0db3f09a1ff47444c773947c6422184b1b445c"},"schema_version":"1.0","source":{"id":"1703.06777","kind":"arxiv","version":1}},"canonical_sha256":"97893e2b6e7b69f195bdca7081de7221b309ac1206eb80d7c24415d3f0c29f1c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97893e2b6e7b69f195bdca7081de7221b309ac1206eb80d7c24415d3f0c29f1c","first_computed_at":"2026-05-18T00:48:21.771803Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:48:21.771803Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mdvdV0N6fy1IiyKHWsyiBjc4yTb0XdWhCizNn2dOXJN7OfjsZ62n090fsVgVKLDILlDgTq58wBlOGzsV8rJcDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:48:21.772608Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.06777","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:80b5f8a969776e0562e41ebc123469bcfd9f4dfdb168d076a6b322baa53d80d9","sha256:3939e083a67e9800f3d46db0fac124e43e5fcf5fd8a128e9438ab7c2e186183a"],"state_sha256":"e5e8dee53df4befe121192db3fa2c25a3d48ecd6bd37e739db75b3f34f900365"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NlJgHyB3mA0zm3PpZ3d0UTn5QFELVlqcpDQNthw75J1IwiHpmO+hMnzBB+YSEKEyv7R4aWIkrk5IY57yOAlXBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T21:05:59.698116Z","bundle_sha256":"637296e480788ce42395510cba6af67ca7bf5e82f2b760aceb5499c6e5058aec"}}