Cargando…
Solvable Model for the Linear Separability of Structured Data
Linear separability, a core concept in supervised machine learning, refers to whether the labels of a data set can be captured by the simplest possible machine: a linear classifier. In order to quantify linear separability beyond this single bit of information, one needs models of data structure par...
| Autor principal: | |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999416/ https://www.ncbi.nlm.nih.gov/pubmed/33806454 http://dx.doi.org/10.3390/e23030305 |