The Shape of Data

In the last post, I discussed the statistical tool called linear regression for different dimensions/numbers of variables and described how it boils down to looking for a distribution concentrated near a hyperplane of dimension one less than the total number of variables (co-dimension one). For two variables this hyperplane is just a line, which is what you may usually think of regression as. In this post, I’ll discuss a more flexible version of regression, in which we allow the line or hyperplane to be curved.

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