Model Selection for Predicting Outcomes of Rescued Raccoon Dogs

5.5 KB of data supporting model selection for predicting outcomes of rescued raccoon dogs. Bong Kyun Kim authored this dataset, which was last updated on 2026-05-28. It applies logistic regression based on Akaike’s Information Criterion (AIC).

Use Cases

• Compare logistic regression models based on AIC scores mentioned in the description.
• Predict release or rehabilitation outcomes for rescued raccoon dogs based on input variables.
• Benchmark model selection techniques in ecological or veterinary data science.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• The 5.5 KB file size suggests a focused, specific analysis.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Freshness

Last updated 2026-05-28 17:31:20; freshness should be verified.