Classifier Performance Metrics for Maxillary Sinus Volume Analysis on 127 Instances

127 instances of classifier performance results, including lower bound, mean, and upper bound values at a 95% confidence level. The results were generated by Çağatay Bölgen using five-fold stratified cross-validation without feature selection. The dataset was last updated on March 18, 2026.

Use Cases

• Benchmarking classifier performance based on metrics provided at a 95% confidence level.
• Comparing model stability using the lower bound, mean, and upper bound values from cross-validation.
• Analyzing machine learning results for volumetric assessment of the maxillary sinus mentioned in the platform tags.

Strengths

• Results are provided with a 95% confidence interval, including lower bound, mean, and upper bound values.
• Methodology is clearly stated as five-fold stratified cross-validation on 127 instances.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 5.5 KB, indicating limited scope.

Provenance

Source

Çağatay Bölgen via figshare

Collection Method

Results obtained from classifiers applied to instances, likely from medical imaging data, using five-fold stratified cross-validation.

Freshness

Last updated 2026-03-18 17:32:24; freshness should be verified.