The interpretability of the results is another critical consideration. Some algorithms, like decision trees, offer high interpretability, making it easier for stakeholders to understand and act on the findings. In contrast, complex models like neural networks might provide higher accuracy but at the cost of interpretability. The choice of algorithm should align with the need for transparency and the ability to communicate findings effectively.
