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Dimensionality reduction refers to techniques for reducing many variables into a smaller number while keeping as much information as possible. One prominent method is [tag pca]

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How can "profiling" be done in a dataset? What are the different techniques?

I am currently doing an analysis in which I need to "profile" each record. For example, let's say I have a dataset of accounts with customer information (name, id, address, money spent, products bough …
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