When selecting an algorithm, it is essential to consider the complexity of the model. Simple models like logistic regression might suffice for straightforward relationships, while more complex scenarios might require advanced techniques such as Bayesian networks or agent-based models. The complexity of the model should align with the study's objectives and the available computational resources.
