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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| Format: | eBook |
| Language: | English |
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Chapman and Hall/CRC
2016
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| Edition: | 1st |
| Series: | Chapman & Hall/CRC Monographs on Statistics & Applied Probability
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| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | 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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| Physical Description: | 251 pages 14 illustrations) |
| ISBN: | 9780367576288 9781466556669 9780429188374 1466556668 1466556684 0429188374 9781466556683 |