Algorithm Performance Indexes for Predictive Mapping of Ticks and Vertebrates

Performance indexes for multiple algorithms used to predict habitats for ticks and vertebrates, which are explanatory variables for Crimean-Congo Hemorrhagic Fever Virus (CCHFV) occurrence. The dataset includes seven model evaluation metrics such as AUC, sensitivity, and Cohen's Kappa. Authored by Agustín Estrada-Peña and last updated on May 27, 2026, it is a 5.5 KB XLS file available under a CC-BY-4.0 license.

Use Cases

• Comparing the predictive performance of different modeling algorithms based on metrics like AUC and omission rate.
• Selecting an optimal habitat threshold for species distribution models based on sensitivity and specificity trade-offs.
• Benchmarking new ecological niche models against established performance metrics such as accuracy and Cohen's Kappa.

Strengths

• Includes seven distinct model performance metrics, providing a multi-faceted evaluation.
• Dataset is openly licensed under CC-BY-4.0, facilitating reuse.
• File size is 5.5 KB, indicating a focused and easily downloadable dataset.

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale analyses.
• 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

Collection Method

Likely derived from the outputs of predictive modeling algorithms for species distribution.

Freshness

Last updated 2026-05-27 17:43:43; freshness should be verified.