# topepo/caret

caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models

Repository: https://github.com/topepo/caret
Canonical: https://ross.abutalabs.com/products/topepo-caret
Homepage: http://topepo.github.io/caret/
Language: R
License Family: other
Last push: 2026-08-24T15:30:15+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 4492, "days_push": 9, "days_rel": 631, "gap_med": null, "n_releases_24m": 1}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1669, forks 627 (observed 2026-08-28T04:05:19.872032+00:00)

## What it is
caret (Classification And Regression Training) is an R package providing a unified interface for training, tuning, and evaluating classification and regression models across many modeling engines. It streamlines data splitting, preprocessing, feature selection, resampling-based parameter tuning, and variable importance estimation.

## Use cases
- train classification and regression models in R with a consistent interface
- tune model hyperparameters using cross-validation or bootstrapping
- split data into training and test sets with proper preprocessing
- estimate variable importance for predictive models
- compare many model types with the same workflow
- select features before fitting a model

## When to choose
- you work in R and want one consistent syntax across dozens of model implementations
- you need systematic resampling-based hyperparameter tuning and model comparison
- you want built-in preprocessing, data splitting, and variable importance in a single package

## When to avoid
- you need actively developed new features - caret is in maintenance mode
- you prefer the newer tidymodels ecosystem (parsnip, tune, workflows) for modern R modeling
- you work primarily in Python or another language

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, data-science, benchmarking
- domain: machine-learning, data-science
- platform: python, cross-platform
- tags: r-package, model-tuning, resampling, feature-selection, preprocessing, unified-model-interface

## Member repositories
- topepo/caret (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:19.872032+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:42:47.992759+00:00, confidence not recorded.
  - readme: https://github.com/topepo/caret (fetched 2026-08-28T04:05:19.872032+00:00, sha e3449e8258e7)
  - homepage: http://topepo.github.io/caret/ (fetched 2026-08-29T11:16:02.444100+00:00, sha 0a6b4be60a4b)
- Data as of 2026-08-30T08:39:29.467469+00:00.