The present work provides a general framework for tree-partitioning problems based on mixed-integer linear programming (MILP). In particular, we present a novel MILP formulation to optimally solve ...

In traditional binary classification tasks, learning algorithms conventionally distinguish positive and negative samples by leveraging fully labeled training data. However, in practical applications, ...