tidymodelstidymodelsOfficialยท2 Agent Skills Included

parsnip

Unified R interface for training machine learning models consistently

Provides a single tidy interface for fitting machine learning models in R across many engines. Eliminates the confusion of learning different argument names and syntax for randomForest, ranger, xgboost, and Spark. Lets users swap model engines and modes with one line, speeding up experimentation and model comparison.
npx skills add tidymodels/parsnip --all -g -y
Available:

Gives the AI agent the exact R commands, coding style rules, testing conventions, and documentation steps to follow when developing or proofreading code in this package.

All Skills in This Repository (2)

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Frequently Asked Questions

FAQPage Schema
How to install parsnip?โ–ผ

Run `npx skills add tidymodels/parsnip --all -g -y` in your terminal to install all skills in this suite globally.

What does parsnip do in R?โ–ผ

Parsnip gives you one consistent interface to train many machine learning models in R, so you can switch between engines like ranger, xgboost, or Spark without rewriting your code.

How do I switch model engines in parsnip?โ–ผ

Define the model once, then call set_engine() with a different engine name such as "ranger" or "spark". The rest of your code stays exactly the same.

Does parsnip work with AI coding agents?โ–ผ

Yes. The included guides teach AI agents the package's testing, documentation, and deprecation workflows so they can contribute correct R code automatically.

Do I need to learn each modeling package's syntax?โ–ผ

No. Parsnip harmonizes argument names across packages, so one argument like `trees` works the same for random forests, boosting, and bagging.

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