Many scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. For example, oncologists classify tumors as different known cancer ...

Abstract: Traditional decision tree algorithms face the problem of having sharp decision boundaries which are hardly found in any real-life classification problems. A fuzzy supervised learning in ...

Abstract: A decision tree is a tree whose internal nodes can be taken as tests (on input data patterns) and whose leaf nodes can be taken as categories (of these patterns). These tests are filtered ...

STreeD is a framework for optimal binary decision trees with separable optimization tasks. A separable optimization task is a task that can be optimized separately for the left and right subtree. The ...

In total, 6 decision tree models were implemented, namely the classification and regression tree (CART), C5.0, GB, XGBoost, AdaBoost algorithm and random forest models. The Shapley additive ...

School of Information, Central University of Finance and Economics, Beijing, China. Personal credit risk is a part that both government and enterprises attach great importance to. A good personal ...