{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "unit8co-darts--backtest-and-compare-forecasting-models-in-darts",
 "repo": "unit8co/darts",
 "repo_url": "https://github.com/unit8co/darts",
 "repo_slug": "unit8co-darts",
 "title": "Compare many models on the same series fairly",
 "page_title": "How to compare many models on the same series fairly with Darts",
 "summary": "Use the shared interface, metrics and backtesting utilities to rank models on historical forecasts.",
 "who": "A team that has to defend which model goes into production.",
 "problem": "Comparing libraries one by one makes results hard to trust.",
 "outcome": "A ranked comparison of models on your own data, using moving time windows.",
 "steps": [
  "Install it with `pip install darts`",
  "Build your TimeSeries and pick candidates from the forecasting models listed in the README, from ARIMA to N-BEATS",
  "Use the backtesting utilities, which the README describes as simulating historical forecasts using moving time windows",
  "Score the runs with the metrics module, from R2-scores to Mean Absolute Scaled Error, and explain the winner with SHAP values where supported"
 ],
 "agent_prompt": "Using unit8co/darts, backtest ARIMA and a deep model on <my series> with moving windows, report the metrics side by side and say which one I should ship.",
 "agents": [
  "claude-code",
  "codex",
  "cursor",
  "gemini-cli"
 ],
 "difficulty": "Intermediate",
 "time": "2 hours",
 "basis": "readme",
 "caveat": "Deep learning models in Darts run on PyTorch Lightning, so training time depends on your hardware.",
 "category": "Data and analytics",
 "tags": [
  "Data and analytics"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.11 or newer, ideally in a clean environment",
  "`pip install darts`",
  "Your series as a pandas DataFrame or one of the supported backends"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/unit8co-darts/backtest-and-compare-forecasting-models-in-darts/",
 "md": "https://dedupedai.com/use-cases/unit8co-darts/backtest-and-compare-forecasting-models-in-darts/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/unit8co-darts--backtest-and-compare-forecasting-models-in-darts.json",
 "api_version": "v1"
}