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Constrained Principal Component Analysis and Related Techniques /
In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? W...
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| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Chapman and Hall/CRC,
2016.
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| Edición: | 1st. |
| Colección: | Chapman & Hall/CRC Monographs on Statistics & Applied Probability.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
| Sumario: | In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? Wha. |
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| Descripción Física: | 1 online resource (251 pages : 14 illustrations). |
| ISBN: | 9781466556683 1466556684 |