Hyperparameter Tables for GBRF and SCO Optimization Frameworks

A 5.5 KB Excel file contains hyperparameter configurations for the GBRF (Gradient Boosting Random Forest) and SCO (Stochastic Combinatorial Optimization) optimization frameworks. It was authored by Dongqi Wei and last updated on April 8, 2026.

Use Cases

• Tune GBRF model performance by selecting hyperparameters from the provided configuration tables.
• Initialize SCO algorithm runs using pre-defined hyperparameter sets to reduce search time.
• Compare the effect of different hyperparameter values on model convergence and accuracy for the specified frameworks.
• Reproduce optimization experiments by using the documented hyperparameter values as a baseline.

Strengths

• Small 5.5 KB file size enables quick download and inspection.
• Clear attribution to a single author under a permissive CC-BY-4.0 license.
• Recent update in April 2026 suggests current relevance for the specified frameworks.

Limitations

• Very small 5.5 KB size indicates limited scope, likely containing only a few parameter configurations.
• Unknown row count and lack of sample data or column descriptions limit understanding of data structure.
• Platform tags only indicate 'Excel', providing no details on the specific hyperparameters included.

Provenance

Source

Dongqi Wei via figshare.

Collection Method

Presumably curated or defined by the author for the specified optimization frameworks.

Freshness

Last updated on 2026-04-08.