Analyzing Limits of Classification Performance with Kullback-Leibler Divergence and Cohen's Kappa

The author explores the fundamental limits of error rates in classification algorithms by relating Kullback-Leibler divergence to Cohen’s Kappa, providing insights into the theoretical best-case performance achievable.