What is the advantage of starting with most fields selected when creating a prediction?

Starting with most fields selected when creating a prediction is beneficial because it ensures that important fields are not excluded from the model. Including a wide range of fields can capture more relevant data and relationships that influence the prediction outcome. This comprehensive approach helps in identifying which variables contribute significantly to the predictive accuracy of the model. Additionally, when more fields are included, there is a higher likelihood of discovering critical patterns or insights that could be vital for making informed predictions.

The process of incrementally refining the selection from this initial broad set allows for optimization, ensuring that key factors driving the predicted outcomes are retained, rather than risk omitting potentially impactful variables. This foundational strategy enhances the robustness of the prediction model.