This skill covers the end-to-end workflow for optimizing DBSCAN clustering of noisy citizen-science annotations against expert ground truth. The goal is to find the Pareto frontier of hyperparameter configurations that trade off between two objectives:
How to install mars-clouds-clustering?
etayang10th/spark-skills/mars-clouds-clustering
$npx -y skills add etayang10th/spark-skills --skill mars-clouds-clusteringInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/etayang10th/spark-skills" --skill "etayang10th/spark-skills/mars-clouds-clustering"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/etayang10th/spark-skills" that are relevant to the current task. Run `npx skills add "https://github.com/etayang10th/spark-skills"` and select the relevant skills, then follow their instructions.
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