Mathematical optimization in classification and regression trees
From MaRDI portal
Publication:828748
DOI10.1007/s11750-021-00594-1zbMath1467.90021OpenAlexW3138703676MaRDI QIDQ828748
Cristina Molero-Río, Dolores Romero Morales, Emilio Carrizosa
Publication date: 5 May 2021
Published in: Top (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11750-021-00594-1
sparsityclassification and regression treescontinuous nonlinear optimizationtree ensemblesexplainabilitymixed-integer linear optimization
Related Items (16)
The backbone method for ultra-high dimensional sparse machine learning ⋮ Variable selection for Naïve Bayes classification ⋮ On sparse optimal regression trees ⋮ Robust optimal classification trees under noisy labels ⋮ Margin optimal classification trees ⋮ Interpretable clustering via soft clustering trees ⋮ On mathematical optimization for clustering categories in contingency tables ⋮ On multivariate randomized classification trees: \(l_0\)-based sparsity, VC dimension and decomposition methods ⋮ On clustering and interpreting with rules by means of mathematical optimization ⋮ On optimal regression trees to detect critical intervals for multivariate functional data ⋮ On sparse ensemble methods: an application to short-term predictions of the evolution of COVID-19 ⋮ Unnamed Item ⋮ Interpretable machine learning: fundamental principles and 10 grand challenges ⋮ Assessment of the influence of features on a classification problem: an application to COVID-19 patients ⋮ A maximum-margin multisphere approach for binary multiple instance learning ⋮ Optimal policy trees
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Greedy function approximation: A gradient boosting machine.
- Multi-class AdaBoost
- A second-order method for strongly convex \(\ell _1\)-regularization problems
- On the asymptotics of random forests
- Supervised classification and mathematical optimization
- Supersparse linear integer models for optimized medical scoring systems
- Auction optimization using regression trees and linear models as integer programs
- Node harvest
- Small area estimation of the homeless in Los Angeles: an application of cost-sensitive stochastic gradient boosting
- Pareto-optimality of oblique decision trees from evolutionary algorithms
- Constructing optimal binary decision trees is NP-complete
- A decision-theoretic generalization of on-line learning and an application to boosting
- HHCART: an oblique decision tree
- Functional-bandwidth kernel for support vector machine with functional data: an alternating optimization algorithm
- Learning customized and optimized lists of rules with mathematical programming
- Visualizing data as objects by DC (difference of convex) optimization
- Optimization approaches to supervised classification
- Forecasting with temporal hierarchies
- A SAT-based approach to learn explainable decision sets
- Multivariate decision trees
- A brief history of linear and mixed-integer programming computation
- Learning decision trees with flexible constraints and objectives using integer optimization
- A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C
- Optimization problems for machine learning: a survey
- Profit driven decision trees for churn prediction
- Distance geometry and data science
- SIRUS: stable and interpretable RUle set for classification
- Column generation based heuristic for learning classification trees
- Sparsity in optimal randomized classification trees
- Explanation in artificial intelligence: insights from the social sciences
- Time series interpolation via global optimization of moments fitting
- On learning and branching: a survey
- Data mining in biomedicine
- Consistency of random forests
- A random forest guided tour
- Global optimization issues in deep network regression: an overview
- Comprehensible credit scoring models using rule extraction from support vector machines
- Selection of time instants and intervals with support vector regression for multivariate functional data
- A Genetic Algorithm-Based Approach for Building Accurate Decision Trees
- Oblique Multicategory Decision Trees Using Nonlinear Programming
- An Optimal Constrained Pruning Strategy for Decision Trees
- Multidimensional Scaling for Genomic Data
- Cost-Sensitive Decision Tree Induction with Label-Dependent Late Constraints
- Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation
- Classification and Regression via Integer Optimization
- Multivariate classification trees based on minimum features discrete support vector machines
- Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
- Optimization Methods for Large-Scale Machine Learning
- Human Decisions and Machine Predictions*
- 10.1162/153244303322753616
- 10.1162/153244303322753751
- Fifty Years of Classification and Regression Trees
- Optimization of Tree Ensembles
- Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization
- When Is the Right Time to Refresh Knowledge Discovered from Data?
- Feature Selection via Coalitional Game Theory
- Optimal classification trees
- Nonlinear optimization and support vector machines
- Optimal classification trees
- Random forests
- Stochastic gradient boosting.
- Linear programming boosting via column generation
This page was built for publication: Mathematical optimization in classification and regression trees
