# \[English help\] An imputer that works with any supervised model, a "GeneralImputer" or a "UniversalImputer" (or other?)

**URL:** <https://discourse.julialang.org/t/english-help-an-imputer-that-works-with-any-supervised-model-a-generalimputer-or-a-universalimputer-or-other/109187>\
**Category:** Machine Learning\
**Created:** [January 24, 2024, 9:09am UTC](https://discourse.julialang.org/t/english-help-an-imputer-that-works-with-any-supervised-model-a-generalimputer-or-a-universalimputer-or-other/109187 "2024-01-24T09:09:48Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![sylvaticus](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sylvaticus/32/203883_2.png) [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Post date:** [January 24, 2024, 9:09am UTC](https://discourse.julialang.org/t/english-help-an-imputer-that-works-with-any-supervised-model-a-generalimputer-or-a-universalimputer-or-other/109187/1 "2024-01-24T09:09:48Z")

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I am standardizing the names of the models on my [Beta Machine Learning Toolkits (BetaML)](https://githubs.com/sylvaticus/BetaML.jl)… concerning the Imputers (of missing values), I have some that use a specific algorithm, e.g. Random Forest, or Gaussian Mixture models (and I call them “RandomForestImputer” and “GaussianMixtureImputer”) but I have one that works with any supervised model (not necessarily from BetaML), as long this has an API of type `Model()`; `a_fit_function()`, `a_predict_function()`. Should I call this Imputer a “GeneralImputer”, “UniversalImputer”, “StandardImputer”, or what else? (I think I would avoid “GenericImputer” as it would imply it doesn’t specialize to one particular situation, while it does a sufficient job on all cases, while here it is the opposite, it can specialise to a particular case given a suitable model)