# Exact Gaussian Process Regression on kegg undir (80 20 train test) Source: [Exact Gaussian Process Regression on kegg undir (80 20 train test)]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:20:56.291Z Evaluation of models performing Exact Gaussian Process Regression on the 80/20 train/test split of the kegg undir dataset, reporting metrics such as RMSE, Final training loss, and Runtime. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Exact Gaussian Process Regression | | Dataset (including any stated split) | kegg undir (80 20 train test) | | Metric | RMSE | | Unit | SCALAR | | Direction | Lower is better | | Results loaded | 0 of 0 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [RMSE](): Lower is better; unit: SCALAR. - [Final Training Loss](): Lower is better; unit: SCALAR. - [Runtime (s/epoch)](): Lower is better; unit: TIME. ## Recorded results | Method | RMSE | Result date | Report paper | | --- | --- | --- | --- | Page 1 of 1. This is an index page, not the full collection.