ClustAll performance against standard clustering algorithms.

A comparative analysis of ClustAll’s performance against standard clustering algorithms across multiple datasets. The "Method" column lists the clustering approaches evaluated, including ClustAll and various combinations of distance metrics and clustering algorithms. "Sensitivity" and "Specificity" columns show the average accuracy of each method in identifying positive and negative cases, respectively, when compared to the known reference column (true labels). These values are calculated across multiple bootstrap samples to ensure reliability. The "Stability" column indicates the consistency of cluster assignments across different bootstrap iterations, with higher values suggesting more robust clustering. Results are provided for three scenarios: the complete breast cancer dataset, the breast cancer dataset with imputed missing values, and the heart attack dataset.