If we were to use the crossover point (similarity ≥ 0.57), we would clearly "infect" the training data with a significant number of misclassified instances, namely 30.69% of the new training instances; this would have an unpredictable impact on classification performance.
if we were to select a higher threshold based on a higher estimated proportion of correctly-classified instances (e.g.