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Random Steinhaus Distances for Robust Syntax-Based Classification of Partially Inconsistent Linguistic Data
We use the Steinhaus transform of metric distances to deal with inconsistency in linguistic classification. We focus on data due to G. Longobardi’s school: languages are represented through yes-no strings of length 53, each string position corresponding to a syntactic feature which can be present or...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274662/ http://dx.doi.org/10.1007/978-3-030-50153-2_2 |