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...
Tallennettuna:
| Julkaisussa: | Polibits |
|---|---|
| Päätekijät: | , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Instituto Politécnico Nacional
2016
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| Aiheet: | |
| Linkit: | https://www.redalyc.org/articulo.oa?id=402646943004 |
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