3 papers
cs.LG2026
Scaling Optimal Classification Trees via Adaptive Feature and Sample Reduction
Jiancheng Tu, Wenqi Fan
Dynamic programming for optimal classification trees becomes computationally expensive as the numbers of features and training samples increase. We develop a joint feature- and sam…
cs.LG2026
Generalized Optimal Classification Trees: A Mixed-Integer Programming Approach
Jiancheng Tu, Wenqi Fan, Zhibin Wu
Global optimization of decision trees is a long-standing challenge in combinatorial optimization, yet such models play an important role in interpretable machine learning. Although…
cs.LG2024
BooleanOCT: Optimal Classification Trees based on multivariate Boolean Rules
Jiancheng Tu, Wenqi Fan, Zhibin Wu
The global optimization of classification trees has demonstrated considerable promise, notably in enhancing accuracy, optimizing size, and thereby improving human comprehensibility…