English

Backtrack Tie-Breaking for Decision Trees: A Note on Deodata Predictors

Machine Learning 2022-02-10 v2
Authors: Cristian Alb
View on arXiv ↗ PDF ↗ DOI ↗

Abstract

A tie-breaking method is proposed for choosing the predicted class, or outcome, in a decision tree. The method is an adaptation of a similar technique used for deodata predictors.

Keywords

decision tree machine learning

Cite

@article{arxiv.2202.03865,
  title  = {Backtrack Tie-Breaking for Decision Trees: A Note on Deodata Predictors},
  author = {Cristian Alb},
  journal= {arXiv preprint arXiv:2202.03865},
  year   = {2022}
}

Related papers

View all related →
Machine Learning · Computer Science
Interfering Paths in Decision Trees: A Note on Deodata Predictors
Cristian Alb
2022-02-25
Machine Learning · Computer Science
Reinforced Decision Trees
Aurélia Léon, Ludovic Denoyer
2015-11-26
Machine Learning · Computer Science
Evaluating Nonlinear Decision Trees for Binary Classification Tasks with Other Existing Methods
Yashesh Dhebar, Sparsh Gupta, Kalyanmoy Deb
2020-08-26
Machine Learning · Computer Science
An Algorithmic Framework for Constructing Multiple Decision Trees by Evaluating Their Combination Performance Throughout the Construction Process
Keito Tajima, Naoki Ichijo, Yuta Nakahara, Toshiyasu Matsushima
2024-02-12
Information Retrieval · Computer Science
Data Mining Applications: A comparative Study for Predicting Student's performance
Surjeet Kumar Yadav, Brijesh Bharadwaj, Saurabh Pal
2012-02-24
Machine Learning · Computer Science
Data Mining: A Prediction for Performance Improvement of Engineering Students using Classification
Surjeet Kumar Yadav, Saurabh Pal
2012-03-20
Machine Learning · Computer Science
Dive into Decision Trees and Forests: A Theoretical Demonstration
Jinxiong Zhang
2021-01-22
Data Analysis, Statistics and Probability · Physics
Boosted decision trees
Yann Coadou
2022-06-22
Machine Learning · Computer Science
A systematic literature review on state-of-the-art deep learning methods for process prediction
Dominic A. Neu, Johannes Lahann, Peter Fettke
2021-06-09
Machine Learning · Computer Science
GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent
Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt
2024-08-20
Machine Learning · Computer Science
Differentially-Private Decision Trees and Provable Robustness to Data Poisoning
Daniël Vos, Jelle Vos, Tianyu Li, Zekeriya Erkin +1
2023-10-13
Methodology · Statistics
Building Trees for Probabilistic Prediction via Scoring Rules
Sara Shashaani, Ozge Surer, Matthew Plumlee, Seth Guikema
2024-06-21
Machine Learning · Computer Science
Explaining Predictions from Tree-based Boosting Ensembles
Ana Lucic, Hinda Haned, Maarten de Rijke
2019-07-08
Artificial Intelligence · Computer Science
Postponing Branching Decisions
Willem Jan van Hoeve, Michela Milano
2007-05-23
Machine Learning · Computer Science
Collapsing the Decision Tree: the Concurrent Data Predictor
Cristian Alb
2021-08-10
Logic in Computer Science · Computer Science
Dynamic Backward Slicing of Rewriting Logic Computations
María Alpuente, Demis Ballis, Javier Espert, Daniel Romero
2011-06-07
Methodology · Statistics
Tree-Structured Modelling of Categorical Predictors in Regression
Gerhard Tutz, Moritz Berger
2015-04-21
Machine Learning · Statistics
Building Ensembles of Adaptive Nested Dichotomies with Random-Pair Selection
Tim Leathart, Bernhard Pfahringer, Eibe Frank
2016-07-06
Machine Learning · Computer Science
Improving the compromise between accuracy, interpretability and personalization of rule-based machine learning in medical problems
Francisco Valente, Jorge Henriques, Simão Paredes, Teresa Rocha +2
2021-10-19
Machine Learning · Computer Science
Improved Information Gain Estimates for Decision Tree Induction
Sebastian Nowozin
2012-06-22
Computation and Language · Computer Science
Wait! There's a Way Out: A Decision Mechanism for Forecasting Conversational Derailment
Laerdon Kim, Vivian Nguyen, Cristian Danescu-Niculescu-Mizil
2026-05-29
Machine Learning · Computer Science
An Experimental Comparison of Old and New Decision Tree Algorithms
Arman Zharmagambetov, Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Magzhan Gabidolla
2020-03-23
Machine Learning · Computer Science
Learning a Decision Tree Algorithm with Transformers
Yufan Zhuang, Liyuan Liu, Chandan Singh, Jingbo Shang +1
2024-08-27
Machine Learning · Computer Science
Tree-Based Dynamic Classifier Chains
Eneldo Loza Mencía, Moritz Kulessa, Simon Bohlender, Johannes Fürnkranz
2021-12-14
Machine Learning · Statistics
Exploiting Categorical Structure Using Tree-Based Methods
Brian Lucena
2020-04-17
R2 v1 2026-06-24T09:26:15.130Z