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tidymodels
recipes:Preprocessing and Feature Engineering Steps for Modeling
A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.
Maintained by Max Kuhn. Last updated 3 days ago.
586 stars 18.80 score 7.2k scripts 383 dependents
r-world-devs
cohortBuilder:Data Source Agnostic Filtering Tools
Common API for filtering data stored in different data models. Provides multiple filter types and reproducible R code. Works standalone or with 'shinyCohortBuilder' as the GUI for interactive Shiny apps.
Maintained by Krystian Igras. Last updated 13 days ago.
8 stars 8.01 score 55 scripts 1 dependents
ropensci
tic:Tasks Integrating Continuously: CI-Agnostic Workflow Definitions
Provides a way to describe common build and deployment workflows for R-based projects: packages, websites (e.g. blogdown, pkgdown), or data processing (e.g. research compendia). The recipe is described independent of the continuous integration tool used for processing the workflow (e.g. 'GitHub Actions' or 'Circle CI'). This package has been peer-reviewed by rOpenSci (v0.3.0.9004).
Maintained by Eli Miller. Last updated 2 months ago.
appveyorcontinuous-integrationdeploymentgithubactionstravis-ci
155 stars 7.57 score 16 scripts