tidymodels

tidymodels is a Model training & evaluation skill for AI agents, published by DAAF-Contribution-Community in the daaf repository on GitHub. Skillspace rates tidymodels D (66/100) and it passed the safety scan; the rating is based on static analysis only.

R machine learning with tidymodels: recipes (preprocessing), parsnip (model specs), workflows (fit pipelines), tune (hyperparameters), rsample (resampling). Engines: ranger (RF), glmnet (lasso/ridge), xgboost, kknn. Model interpretation (permutation importance, PDP/ICE, SHAP via DALEX/iml/kernelshap) and fairness assessment (fairmodels). UMAP via uwot. Use when execution language is R. Python equivalent: scikit-learn. For econometric regression use fixest or r-stats.

Grade
D
Quality
66 / 100
Safety
Passed
GitHub stars
220

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubDAAF-Contribution-Community/daaf

Our review

Architecture
84 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
LGPL-3.0
Adoption
Adopted by 0 other repositories, in 0 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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