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A Memory-Efficient Encoding Method for Processing Mixed-Type Data on Machine Learning
The most common machine-learning methods solve supervised and unsupervised problems based on datasets where the problem’s features belong to a numerical space. However, many problems often include data where numerical and categorical data coexist, which represents a challenge to manage them. To tran...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763608/ https://www.ncbi.nlm.nih.gov/pubmed/33316972 http://dx.doi.org/10.3390/e22121391 |