"Use Surprise for explicit-feedback recommender workflows: load
Scanned 9/9/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill surprise --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Surprise?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-surprise)More formats (shields.io, HTML) on the badges page.
---
name: surprise
description: "Use Surprise for explicit-feedback recommender workflows: load
rating data, fit collaborative-filtering predictors, evaluate and tune models,
generate recommendations, and serialize results."
disable-model-invocation: true
metadata:
disco-role: operating
license: BSD 3-Clause
---
# Surprise
Use this skill when a task involves `scikit-surprise` / `surprise`, explicit rating recommendation, collaborative filtering, rating prediction, dataset loading, evaluation and search, top-N ranking, or serialization.
## Start Here
- Install with `pip install scikit-surprise`.
- Add `pandas` when you need dataframe loading or the bundled smoke script's optional fit/test check.
- Add `pytest` only for repository verification or local native smoke runs.
- Run [`scripts/check_surprise_environment.py`](scripts/check_surprise_environment.py) for a safe local import/version/CLI check. Use `--smoke-fit` when pandas is available and you want a tiny end-to-end fit/test check.
- For CLI discovery, use `surprise --help` or `python -m surprise --help`.
## Route by Task
- Load, inspect, validate, or split rating data: [`sub-skills/data-loading/`](sub-skills/data-loading/SKILL.md)
- Choose and configure predictors, fit/test/predict, inspect baseline or similarity options, retrieve neighbors, or build a custom `AlgoBase`: [`sub-skills/prediction-algorithms/`](sub-skills/prediction-algorithms/SKILL.md)
- Score predictions, split data, cross-validate, tune hyperparameters, inspect `cv_results`, or use the CLI: [`sub-skills/evaluation-and-search/`](sub-skills/evaluation-and-search/SKILL.md)
- Build top-N recommendations, precision/recall@k summaries, or dump/load roundtrips: [`sub-skills/recommendation-and-analysis/`](sub-skills/recommendation-and-analysis/SKILL.md)
## Shared References
- Read [`references/overview.md`](references/overview.md) for the package/module map and common data flow.
- Read [`references/troubleshooting.md`](references/troubleshooting.md) for install, data, id, evaluation, search, CLI, and serialization pitfalls.
- Read [`references/repo-provenance.md`](references/repo-provenance.md) before deciding whether this skill still matches the current checkout.
## Boundaries
This is a runtime user skill, not a maintainer guide. It does not cover docs builds, benchmark generation, or release publishing.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!