evaluate-ml-pipeline

evaluate-ml-pipeline is a Model training & evaluation skill for AI agents, published by probabl-ai in the skills repository on GitHub. Skillspace rates evaluate-ml-pipeline D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Methodology for evaluating a single sklearn-compatible learner (in particular, the `SkrubLearner` produced by `build-ml-pipeline`). Owns: which entry point to call (`skore.evaluate` first, the explicit report classes when needed), which cross-validator to pick from scikit-learn's catalogue, how to consume the structural metadata (`groups`, `times`, …) attached at build time via `.skb.mark_as_X(split_kwargs=...)`. Stops at "what does the report say". Defaults (metrics, plots) come from skore; only override on explicit user request. TRIGGER when: code calls `cross_val_score`, `cross_validate`, `classification_report`, or any handwritten metric print (`print(mean_squared_error(...))`); code calls `.skb.cross_validate(...)` (route through skore for richer output); user asks how to score, evaluate, or compare a single learner; user asks how to pick a cross-validator; user wants to see a report / metrics / diagnostic plots for a fitted learner. SKIP when: declaring the pipeline (use…

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

70

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.

Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.