what is a good response to the following post made by a classmate? Neural networks are a type of predictive model that is particularly flexible and capable of modeling complex relationships. Consequently, they also require significant computational power. Regression analysis is best suited for situations requiring simplicity. However, its drawback is its struggle with non-linear data. Decision trees can be considered a middle ground between neural networks and regression analysis. Decision tree models do not require the infrastructure that neural networks might need, and they are also capable of handling non-linear data. As a result of their capability to address aspects lacking in the other two models, decision tree models do not excel at either. Therefore, when choosing a predictive model, it is best to determine the specific needs for a particular project as well as the resources available for allocation