{"paper":{"title":"Inference of a Dyadic Measure and its Simplicial Geometry from Binary Feature Data and Application to Data Quality","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.CA","authors_text":"Linda Ness","submitted_at":"2017-04-29T19:16:51Z","abstract_excerpt":"We propose a new method for representing data sets with a set of binary feature functions. We compute both the dyadic set structure determined by an order on the binary features together with the canonical product coefficient parameters for the associated dyadic measure and a variant of a nerve simplicial complex determined by the support of the dyadic measure together with its betti numbers. The product coefficient parameters characterize the relative skewness of the dyadic measure at dyadic scales and localities. The more abstract betti number statistics summarize the simplicial geometry of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.00970","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"}