What component controls the number of cases used to build a model in the adaptive system?

The component that controls the number of cases used to build a model in the adaptive system is the memory setting on the settings tab. This memory setting determines how many historical cases are retained for analysis and model building. By configuring this setting, you can influence the performance and accuracy of the predictive models developed by the adaptive system. A larger memory setting allows the system to utilize a more extensive dataset, which can lead to improved model effectiveness as it has access to more varied past cases for learning and adjustment.

The other options provide valuable functionality in the adaptive system but do not directly control the number of cases used during model construction. The analysis criteria defined by the user help refine the focus of the model but do not limit the case count. The algorithm type selected pertains to the method used for analysis rather than the dataset size. The data retention policy outlines how long data is kept, which can indirectly influence the number of cases available but does not directly control them in the same manner as the memory setting does.