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Results tagged with pca
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user 71393
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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How to determine which variables need to be trimmed in PCA or Factor analysis?
I want to use PCA to reduce these into principal components (Internet companies, software developers, circuit board manufacturers, etc), which then are to be used as sector-related indices. …
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