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I am interested in predicting a continuous variable reflecting vegetative production using a collection of land use categorical variables. The dataset is a pixel-level dataset, where each pixel has a value of vegetative production and a land use categorization. There are 50+ land use categories and I want to reduce this to a smaller number. I'd like to perform dimension reduction on the land use categories based on their contribution to overall variance in vegetative production. As far as I can tell, MCA won't work unless I bin vegetative production and make it categorical. Any thoughts on how to perform dimension reduction on categorical variables based on values of a continuous variable would be greatly appreciated.

To be clear - I'm interested in the construction of the matrix required and the package to process the matrix either in R or Python. Thanks!

Emily
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  • Are you asking about the math, or are you looking for hints in a particular programming environment? If the latter, you should at least say which programming language/environment you're using. – Chris Tavares Apr 08 '16 at 17:25

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