Which classification model uses splits on a tree to assign inmates to categories?

The decision tree classification model is the correct choice because it employs a tree-like structure where each internal node represents a test on an attribute, each branch represents the outcome of the test, and each leaf node signifies a category or class label. In the context of assigning inmates to categories, a decision tree can analyze various attributes such as behavior, offense type, or risk factors to make informed decisions about classification. The hierarchical nature of the decision tree allows for a clear and systematic approach to classification, making it easy to follow the rationale behind the categorization of inmates.

Other models mentioned, like dynamic and static models, typically represent different methodological approaches to processing data but do not specifically utilize a tree structure for classification purposes. A matrix model, while it can organize data effectively, does not inherently apply the split and decision-making process characteristic of decision trees.