Classification Tree

Classification trees are hierarchical models used for supervised learning, aiming to build accurate and interpretable predictive models by recursively partitioning data based on feature values. Current research focuses on improving the accuracy and efficiency of tree construction, exploring both heuristic methods like CART and increasingly sophisticated optimization techniques, including mixed-integer programming and evolutionary algorithms, to find optimal or near-optimal tree structures. These advancements, along with explorations into handling high-dimensional data and incorporating constraints, are enhancing the performance and applicability of classification trees across various domains, particularly where interpretability is crucial.

Papers

October 14, 2024

TRESTLE: A Model of Concept Formation in Structured Domains
Christopher J. MacLellan, Erik Harpstead, Vincent Aleven, Kenneth R. Koedinger
Full Model Hierarchical Classification Human Learning Classification Tree Concept Formation Classification Paradigm Structured Domain

September 26, 2024

Enriched Functional Tree-Based Classifiers: A Novel Approach Leveraging Derivatives and Geometric Features
Fabrizio Maturo, Annamaria Porreca
Random Forest Novel Approach Geometric Feature Tree Based Functional Data Analysis Classification Tree Derivative Process

August 23, 2024

Augmented Functional Random Forests: Classifier Construction and Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations
Fabrizio Maturo, Annamaria Porreca
Functional Data Analysis Permutation Importance Classification Tree Learning Classifier Functional Principal Component

April 15, 2024

Classification Tree-based Active Learning: A Wrapper Approach
Ashna Jose, Emilie Devijver, Massih-Reza Amini, Noel Jakse, Roberta Poloni
Classification Code Active Learning Supervised Machine Learning Classification Tree

March 28, 2024

Finding Decision Tree Splits in Streaming and Massively Parallel Models
Huy Pham, Hoang Ta, Hoa T. Vu
Decision Tree Data Stream Model Parallelism Streaming Algorithm Online Streaming Classification Tree Optimal Split

January 29, 2024

BooleanOCT: Optimal Classification Trees based on multivariate Boolean Rules
Jiancheng Tu, Wenqi Fan, Zhibin Wu
Random Forest Classification Tree Optimal Classification Tree Boolean Rule Boolean Question

November 12, 2023

A GPU-Accelerated Moving-Horizon Algorithm for Training Deep Classification Trees on Large Datasets
Jiayang Ren, Valentín Osuna-Enciso, Morimasa Okamoto, Qiangqiang Mao, Chaojie Ji, Liang Cao, Kaixun Hua, Yankai Cao
Decision Tree Differential Evolution Large Datasets Classification Tree Tree Structure Horizon Estimation

August 22, 2023

An improved column-generation-based matheuristic for learning classification trees
Krunal Kishor Patel, Guy Desaulniers, Andrea Lodi
Machine Learning Decision Tree Classification Problem Column Generation Classification Tree

June 1, 2023

Loss-Optimal Classification Trees: A Generalized Framework and the Logistic Case
Tommaso Aldinucci, Matteo Lapucci
Loss Function Interpretable Machine Learning Logistics System Generalized Framework Classification Tree Optimal Classification Tree Interpretability Benefit

May 13, 2023

A Novel Memetic Strategy for Optimized Learning of Classification Trees
Tommaso Aldinucci
Interpretable Machine Learning Greedy Approach Learning Problem Optimal Learning Classification Tree

May 7, 2023

Classification Tree Pruning Under Covariate Shift
Nicholas Galbraith, Samory Kpotufe
Edge Pruning Covariate Shift Cross Validation Classification Tree Heterogeneous Training Sparse Decision Tree

April 21, 2023

Rolling Lookahead Learning for Optimal Classification Trees
Zeynel Batuhan Organ, Enis Kayış, Taghi Khaniyev
Near Optimality Machine Learning Application Classification Tree Optimal Classification Tree Lookahead Decoding Lookahead Heuristic

April 11, 2023

Optimal Interpretability-Performance Trade-off of Classification Trees with Black-Box Reinforcement Learning
Hector Kohler, Riad Akrour, Philippe Preux
Reinforcement Learning Inherent Interpretability Markov Decision Process Decision Tree Classification Tree

March 17, 2023

QUBO Decision Tree: Annealing Machine Extends Decision Tree Splitting
Koichiro Yawata, Yoshihiro Osakabe, Takuya Okuyama, Akinori Asahara
Decision Tree Quadratic Unconstrained Binary Regression Tree Annealing Machine Classification Tree Computational Limit

February 14, 2023

Scalable Optimal Multiway-Split Decision Trees with Constraints
Shivaram Subramanian, Wei Sun
Decision Tree Potential Scalability Participation Constraint Mixed Integer Classification Tree

December 9, 2021

On multivariate randomized classification trees: $l_0$-based sparsity, VC~dimension and decomposition methods
Edoardo Amaldi, Antonio Consolo, Andrea Manno
Decision Tree Sparsity Increase Multivariate Approach Decomposition Method Classification Tree VC Dimension Optimal Classification Tree Convex Approximation

December 5, 2021

Face Trees for Expression Recognition
Mojtaba Kolahdouzi, Alireza Sepas-Moghaddam, Ali Etemad
Jina Embeddings Facial Expression Expression Recognition Facial Landmark Classification Tree

November 16, 2021

Multiclass Optimal Classification Trees with SVM-splits
Víctor Blanco, Alberto Japón, Justo Puerto
Split Learning Classification Algorithm Tree Based Classification Tree Optimal Classification Tree