{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:EXF37NY6ZRCQQBK3BCBMSYZKEP","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":"db04b6689602808e4ffc8bbb1717db017f5e853e94259a0da21fc5043aeb4220","cross_cats_sorted":["cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-12-08T20:35:46Z","title_canon_sha256":"8822d2ad24fe7f368922e6cffc7d8e0e20ad621b71e303a2b4654f9d100ae702"},"schema_version":"1.0","source":{"id":"1612.02802","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.02802","created_at":"2026-05-18T00:39:28Z"},{"alias_kind":"arxiv_version","alias_value":"1612.02802v2","created_at":"2026-05-18T00:39:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.02802","created_at":"2026-05-18T00:39:28Z"},{"alias_kind":"pith_short_12","alias_value":"EXF37NY6ZRCQ","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_16","alias_value":"EXF37NY6ZRCQQBK3","created_at":"2026-05-18T12:30:15Z"},{"alias_kind":"pith_short_8","alias_value":"EXF37NY6","created_at":"2026-05-18T12:30:15Z"}],"graph_snapshots":[{"event_id":"sha256:a05a5b90c46ca587708581b3e67ce23316861aede7674ad2ef71f7b0f6f24a65","target":"graph","created_at":"2026-05-18T00:39:28Z","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":"Regression under the \"small $n$, large $p$\" conditions, of small sample size $n$ and large number of features $p$ in the learning data set, is a recurring setting in which learning from data is difficult. With prior knowledge about relationships of the features, $p$ can effectively be reduced, but explicating such prior knowledge is difficult for experts. In this paper we introduce a new method for eliciting expert prior knowledge about the similarity of the roles of features in the prediction task. The key idea is to use an interactive multidimensional-scaling (MDS) type scatterplot display o","authors_text":"Homayun Afrabandpey, Samuel Kaski, Tomi Peltola","cross_cats":["cs.HC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-12-08T20:35:46Z","title":"Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.02802","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:d6d15f552603a198c8a6950f662271e95d5ec680ebc86025ea5543764ad0d5af","target":"record","created_at":"2026-05-18T00:39:28Z","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":"db04b6689602808e4ffc8bbb1717db017f5e853e94259a0da21fc5043aeb4220","cross_cats_sorted":["cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-12-08T20:35:46Z","title_canon_sha256":"8822d2ad24fe7f368922e6cffc7d8e0e20ad621b71e303a2b4654f9d100ae702"},"schema_version":"1.0","source":{"id":"1612.02802","kind":"arxiv","version":2}},"canonical_sha256":"25cbbfb71ecc4508055b0882c9632a23d193308d8c543846c65a6b703078ebf5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"25cbbfb71ecc4508055b0882c9632a23d193308d8c543846c65a6b703078ebf5","first_computed_at":"2026-05-18T00:39:28.849985Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:28.849985Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2hICY9xprRbdLdch7+QPKrtBg/FKfjW0h5tQdj/IAZY/32gicoUOeQRGs1p8xrSPpt+d2ozCYEf3zbvWUg3PCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:28.850703Z","signed_message":"canonical_sha256_bytes"},"source_id":"1612.02802","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d6d15f552603a198c8a6950f662271e95d5ec680ebc86025ea5543764ad0d5af","sha256:a05a5b90c46ca587708581b3e67ce23316861aede7674ad2ef71f7b0f6f24a65"],"state_sha256":"66783ce20e87c357809a684d2deb6da5c0a12b06c5f60250a1a78f2b27bcadad"}