{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:Y7HCH7KNM5MVJU2EH5OXWKCWZQ","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":"30522fefe2ef00f3ba45018bdea31e38bc68ad1252cfd04df6be9347adaae7ca","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-29T00:21:56Z","title_canon_sha256":"2fa93c865f1da18b77025ac5fc1fe4f1d3e5a5fecf23f797c42bb60e444cb428"},"schema_version":"1.0","source":{"id":"2305.19132","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.19132","created_at":"2026-07-05T06:15:38Z"},{"alias_kind":"arxiv_version","alias_value":"2305.19132v1","created_at":"2026-07-05T06:15:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.19132","created_at":"2026-07-05T06:15:38Z"},{"alias_kind":"pith_short_12","alias_value":"Y7HCH7KNM5MV","created_at":"2026-07-05T06:15:38Z"},{"alias_kind":"pith_short_16","alias_value":"Y7HCH7KNM5MVJU2E","created_at":"2026-07-05T06:15:38Z"},{"alias_kind":"pith_short_8","alias_value":"Y7HCH7KN","created_at":"2026-07-05T06:15:38Z"}],"graph_snapshots":[{"event_id":"sha256:2ba536c691b51902e86af4b4a8f3b054ee77f2adaca0710984027e3b2e02cee4","target":"graph","created_at":"2026-07-05T06:15:38Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2305.19132/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study explores a new methodology for machine learning classification tasks in 2-dimensional visualization space (2-D ML) using Visual knowledge Discovery in lossless General Line Coordinates. It is shown that this is a full machine learning approach that does not require processing n-dimensional data in an abstract n-dimensional space. It enables discovering n-D patterns in 2-D space without loss of n-D information using graph representations of n-D data in 2-D. Specifically, this study shows that it can be done with static and dynamic In-line Based Coordinates in different modifications,","authors_text":"Boris Kovalerchuk, Hoang Phan","cross_cats":["cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-29T00:21:56Z","title":"Full High-Dimensional Intelligible Learning In 2-D Lossless Visualization Space"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.19132","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:ad2abd73dc9c0dbe409f769b822eb4ff28f6eba01a12ef2077bd31e6b2051bb7","target":"record","created_at":"2026-07-05T06:15:38Z","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":"30522fefe2ef00f3ba45018bdea31e38bc68ad1252cfd04df6be9347adaae7ca","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-29T00:21:56Z","title_canon_sha256":"2fa93c865f1da18b77025ac5fc1fe4f1d3e5a5fecf23f797c42bb60e444cb428"},"schema_version":"1.0","source":{"id":"2305.19132","kind":"arxiv","version":1}},"canonical_sha256":"c7ce23fd4d675954d3443f5d7b2856cc117ca00656adf8f54dfe07b04ce1dc27","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c7ce23fd4d675954d3443f5d7b2856cc117ca00656adf8f54dfe07b04ce1dc27","first_computed_at":"2026-07-05T06:15:38.767593Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:15:38.767593Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IAYDhaNxOnpqrX6MQ4qQj3pebvXeNdgYDAYSerb8uj/Iju1D3WJQRyhRaCyfpR+WfmMVaIR7OMqJl2rQZqOlDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:15:38.767998Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.19132","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ad2abd73dc9c0dbe409f769b822eb4ff28f6eba01a12ef2077bd31e6b2051bb7","sha256:2ba536c691b51902e86af4b4a8f3b054ee77f2adaca0710984027e3b2e02cee4"],"state_sha256":"38d51afd60ba71e5a1d92ac653aa250f376f70140ecb33a81c79698fa52f378d"}