Confusion Matrices for Real-World and Ideal-World Model Analyses

Confusion matrices for real-world and ideal-world analyses are provided in a 5.5 KB Excel file. The dataset was authored by Karina Lumy Okita and last updated on May 27, 2026. Its specific application context and data collection method are not detailed in the provided metadata.

Use Cases

• Calculate standard classification metrics like accuracy, precision, and recall based on the confusion matrices.
• Compare model performance in real-world scenarios versus ideal-world conditions based on the described analysis types.
• Teach or illustrate the construction and interpretation of confusion matrices for binary or multi-class classification.
• Benchmark a new classification model's error patterns against provided real-world examples.

Strengths

• Dataset is openly licensed under CC-BY-4.0, permitting sharing and adaptation.
• File size is 5.5 KB, ensuring quick download and easy inspection.

Limitations

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

Provenance

Source

Karina Lumy Okita via figshare

Freshness

Last updated 2026-05-27 17:49:56; freshness should be verified.