# Is there any julia package for multivariate polynomial regression?

**URL:** <https://discourse.julialang.org/t/is-there-any-julia-package-for-multivariate-polynomial-regression/108785>\
**Category:** Machine Learning\
**Tags:** question, package\
**Created:** [January 14, 2024, 6:02am UTC](https://discourse.julialang.org/t/is-there-any-julia-package-for-multivariate-polynomial-regression/108785 "2024-01-14T06:02:49Z")\
**Posts on this page:** 1\
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**Author:** ![Mattriks](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mattriks/32/351_2.png) [@Mattriks](https://discourse.julialang.org/u/Mattriks)\
**Post date:** [January 14, 2024, 6:38pm UTC](https://discourse.julialang.org/t/is-there-any-julia-package-for-multivariate-polynomial-regression/108785/12 "2024-01-14T18:38:09Z")

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[CoupledFields.jl](https://github.com/Mattriks/CoupledFields.jl) can also do high dimensional polynomial regression. It’s based on [kernel ridge regression](https://discourse.julialang.org/t/smooth-delta-functions-to-compute-jacobian-and-hessian-from-samples/45282/10), and finds the directions of the active subspace via a kernel matrix. Both X and Y can be multivariable.

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