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Results tagged with pca
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user 66519
Principal component analysis (PCA) is a linear dimensionality reduction technique. It reduces a multivariate dataset to a smaller set of constructed variables preserving as much information (as much variance) as possible. These variables, called principal components, are linear combinations of the input variables.
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PCA/factor analysis of mixed (quantitative + qualitative) data: inconsistent results
I tried to apply first a PCA on the 4 variables (forcing the ordinal into numerical which is sometimes suggested), i get this graph:
then i tried to do a FAMD (factor analysis of mixed data) which … It seems from the data (and the PCA) that quanti2 and quali2 should be closely related, but that's not what shows the famd's variable plot. Why so? …
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