Figure 5.

Confusion matrices relative to the classification results for the two benchmark models as well as the classification using the $\mathsf{\Lambda }$ metric. Besides needing fewer data, we observe that the quantity $\mathsf{\Lambda }$ has a higher accuracy $93.9\%$ compared to $72.5\%$ and $86.8\%$ of benchmark1 and benchmark2 respectively. Relative to the other measures, the $\mathsf{\Lambda }$ classification also outperforms the benchmarks, with sensitivity, specificity and precision values of $95.1\%$, $93.1\%$ and $89.6\%$ respectively, compared to the values of $68.9\%$$74.4\%$, $59.0\%$ for the same metrics for benchmark1 and $82.5\%$$89.9\%$, $85.7\%$ for benchmark2.