Machine Learning Model Performance Across Four Grid-Based Spatial Covariate Designs

Four distinct grid-based spatial covariate designs were evaluated across four machine learning algorithms. The dataset, shared by Gustavo Vieira Veloso on figshare, contains results from this systematic evaluation. It was last updated on May 11, 2026.

Use Cases

• Compare model performance based on a 2x2 moving window covariate design
• Analyze the impact of a 10x10 window covariate design on algorithm results
• Benchmark four machine learning algorithms across different spatial covariate scales

Strengths

• Systematic evaluation across four distinct covariate designs (2x2, 5x5, 7x7, 10x10)
• Results from four different machine learning algorithms are included

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment

Provenance

Source

Gustavo Vieira Veloso

Freshness

Last updated 2026-05-11 17:52:10