Glm metrics
How to calculate and save GLM performance metrics (RMSE) to metrics.json. Use this whenever the user asks for RMSE checks or final model evaluation.From its SKILL.md
npx -y skills add cxcscmu/SkillLearnBench --skill glm-metricsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
1.0 KB, 194 tokens by cl100k_base, as published. Nobody here has run it
GLM Performance Metrics
Metrics to Compute
Calculate the following metrics to evaluate the model performance:
overall_rmse: Total RMSE across all matched depth/time pairs.annual_deep_rmse: RMSE for depths >= 13 m.summer_deep_rmse: RMSE for months June-September, depths >= 13 m.overall_n_pairs: Number of total matches.annual_deep_n_pairs: Number of deep matches.summer_deep_n_pairs: Number of summer deep matches.
Requirements
- Data: Match
/root/field_temp_oxy.csvwith simulation output/root/output/output.nc. - Matching method: Exact
datetime+ rounded-depth merge. - Do NOT use nearest-time matching, interpolation, or alternative binning.
Output
Save the metrics as a JSON file at /root/metrics.json with keys named exactly as above.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.