Ridge Regression - where to apply priors?

facebookexperimental / Robyn

Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

https://facebookexperimental.github.io/Robyn/

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Ridge Regression - where to apply priors? #72

Closed fedemendez1 closed 3 years ago

fedemendez1 commented 3 years ago

Hi Team, regarding ridge regression, was wondering if it's possible to choose what prior (weight) to apply to each of the variables? Would be useful to force in variables that the model dropped from the model (coef=0) Thanks

gufengzhou commented 3 years ago

Hi, this can be achieved by using the parameter penalty.factor in glmnet, see the library documentation here. Robyn doesn't provide direct interface for this parameter yet, so you have to modify the model yourself for now.