Recipes Feature Engineering Patterns

What problem does it solve?

Automatically standardizes and accelerates feature engineering workflows in R by providing ready-to-use recipes steps for numeric, categorical, and text data while preventing information leakage and enabling reproducible pipelines.

Core Features & Use Cases

• Provides a library of recipe steps for normalization, imputation, encoding, transformation, and feature selection.
• Enforces best-practice step ordering to improve robustness and auditability of preprocessing in machine learning workflows.
• Use case: data scientists can compose reliable preprocessing pipelines for tabular data in R, streamlining model development and deployment across projects.

Quick Start

Create a preprocessing recipe from the provided patterns and apply it to new data to produce ready-to-model features.