Data Reduction and Regression Using Principal Component Analysis in Qualitative Spatial Reasoning and Health Informatics
The central idea of principal component analysis (PCA) is to reduce the dimensionality of a dataset consisting of a large number of interrelated variables, while retaining as much as possible of the variation present in the dataset . In this paper, we use PCA bas...
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| Publicado no: | Polibits |
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| Principais autores: | , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Instituto Politécnico Nacional
2016
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| Acesso em linha: | https://www.redalyc.org/articulo.oa?id=402646943004 |
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