Supervised Learning Model Performance Metrics for Coffee Rust Prediction

5.5 KB of performance metrics for supervised learning models predicting coffee rust incidence, authored by Maurice Wanyonyi. The dataset is available in XLS format and was last updated on April 21, 2026. It is licensed under CC-BY-4.0.

Use Cases

• Benchmarking machine learning models for agricultural disease prediction based on the described performance metrics.
• Comparing the efficacy of different supervised learning algorithms for coffee rust forecasting.
• Training educational models on crop disease prediction using a small, focused dataset of model results.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Explicitly licensed under the permissive CC-BY-4.0 license.
• Last update date (2026-04-21) is provided.

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, authored by Maurice Wanyonyi.

Collection Method

Likely contains aggregated results from model evaluation experiments.

Time Range

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Freshness

Last updated 2026-04-21 17:43:25; freshness should be verified.

Geography

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