Constrained Principal Component Analysis and Related Techniques
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| Title: | Constrained Principal Component Analysis and Related Techniques |
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| Description: | 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 |
| Authors: | Yoshio Takane |
| Resource Type: | eBook. |
| Subjects: | Principal components analysis, Multivariate analysis, MATHEMATICS / Probability & Statistics / General |
| Categories: | MATHEMATICS / Probability & Statistics / Multivariate Analysis, MATHEMATICS / Probability & Statistics / Regression Analysis |
| Database: | eBook Collection (EBSCOhost) |
| Abstract: | 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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| ISBN: | 9781466556669 9780367576288 9781466556683 9780429188374 9781040079454 |
