Integer and combinatorial optimization
Integer and combinatorial optimization
Inferring decision trees using the minimum description length principle
Information and Computation
Linear programming and network flows (2nd ed.)
Linear programming and network flows (2nd ed.)
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Optimal pruning for tree-structured vector quantization
Information Processing and Management: an International Journal - Special issue on data compression for images and texts
Feature minimization within decision trees
Computational Optimization and Applications
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
A Dynamic Programming Based Pruning Method for Decision Trees
INFORMS Journal on Computing
Parallel Genetic Programming for Decision Tree Induction
ICTAI '01 Proceedings of the 13th IEEE International Conference on Tools with Artificial Intelligence
On growing better decision trees from data
On growing better decision trees from data
A Genetic Algorithm-Based Approach for Building Accurate Decision Trees
INFORMS Journal on Computing
Simplifying decision trees: A survey
The Knowledge Engineering Review
Diversification for better classification trees
Computers and Operations Research
Improving induction decision trees with parallel genetic programming
EUROMICRO-PDP'02 Proceedings of the 10th Euromicro conference on Parallel, distributed and network-based processing
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This paper is concerned with the optimal constrained pruning of decision trees. We present a novel 0--1 programming model for pruning the tree to minimize some general penalty function based on the resulting leaf nodes, and show that this model possesses a totally unimodular structure that enables it to be solved as a shortest-path problem on an acyclic graph. Moreover, we prove that this problem can be solved in strongly polynomial time while incorporating an additional constraint on the number of residual leaf nodes. Furthermore, the framework of the proposed modeling approach renders it suitable to accommodate different (multiple) objective functions and side-constraints, and we identify various such modeling options that can be applied in practice. The developed methodology is illustrated using a numerical example to provide insights, and some computational results are presented to demonstrate the efficacy of solving generically constrained problems of this type. We also apply this technique to a large-scale transportation analysis and simulation system (TRANSIMS), and present related computational results using real data to exhibit the flexibility and effectiveness of the proposed approach.