To tune or not to tune the number of trees in random forest?

16 May 2017

Papers citing "To tune or not to tune the number of trees in random forest?"

42 / 42 papers shown

Title
When do Random Forests work? C. Revelas O. Boldea B. J. M. Werker 84 0 0 17 Apr 2025
Can a Single Tree Outperform an Entire Forest? Qiangqiang Mao Yankai Cao 100 2 0 26 Nov 2024
Bootstrap Sampling Rate Greater than 1.0 May Improve Random Forest Performance Stanisław Kaźmierczak Jacek Mańdziuk 44 0 0 05 Oct 2024
Free Lunch in the Forest: Functionally-Identical Pruning of Boosted Tree Ensembles Youssouf Emine Alexandre Forel Idriss Malek Thibaut Vidal 107 0 0 28 Aug 2024
Adapting tree-based multiple imputation methods for multi-level data? A simulation study Ketevan Gurtskaia Jakob Schwerter Philipp Doebler Markus Pauly Philipp Doebler AI4CE 117 0 0 25 Jan 2024
Are Ensembles Getting Better all the Time? Pierre-Alexandre Mattei Damien Garreau OOD FedML 121 1 0 29 Nov 2023
Linear time Evidence Accumulation Clustering with KMeans G. Candel 18 0 0 15 Nov 2023
The theoretical limits of biometry G. Candel CVBM 17 0 0 06 Nov 2023
Does it pay to optimize AUC? Baojian Zhou Steven Skiena 88 0 0 02 Jun 2023
Heterogeneous Oblique Double Random Forest M. A. Ganaie M. Tanveer I. Beheshti N. Ahmad Ponnuthurai Nagaratnam Suganthan 20 2 0 13 Apr 2023
Benchmarking optimality of time series classification methods in distinguishing diffusions Zehong Zhang Fei Lu Esther Xu Fei Terry Lyons Yannis G. Kevrekidis Tom Woolf AI4TS 80 0 0 30 Jan 2023
Distributional Adaptive Soft Regression Trees Nikolaus Umlauf Nadja Klein 33 1 0 19 Oct 2022
Adaptive deep learning for nonlinear time series models Daisuke Kurisu Riku Fukami Yuta Koike AI4TS 72 6 0 06 Jul 2022
Adversarial random forests for density estimation and generative modeling David S. Watson Kristin Blesch Jan Kapar Marvin N. Wright GAN 122 21 0 19 May 2022
Machine Learning to Support Triage of Children at Risk for Epileptic Seizures in the Pediatric Intensive Care Unit Raphael Azriel Cecil D. Hahn Thomas De Cooman S. Van Huffel E. Payne Kristin McBain Danny Eytan Joachim A. Behar 24 6 0 11 May 2022
AutoScore-Ordinal: An interpretable machine learning framework for generating scoring models for ordinal outcomes S. Saffari Yilin Ning F. Xie Bibhas Chakraborty V. Volovici Roger Vaughan M. Ong Nan Liu LM&MA 27 10 0 17 Feb 2022
A Survey on Automated Sarcasm Detection on Twitter Bleau Moores Vijay K. Mago 44 14 0 05 Feb 2022
Geometry- and Accuracy-Preserving Random Forest Proximities Jake S. Rhodes Adele Cutler Kevin R. Moon 93 83 0 29 Jan 2022
Machine Learning-based Prediction of Porosity for Concrete Containing Supplementary Cementitious Materials C. Cao 52 33 0 13 Dec 2021
Oblique and rotation double random forest M. A. Ganaie M. Tanveer Ponnuthurai Nagaratnam Suganthan V. Snás̃el 24 49 0 03 Nov 2021
Noise-Resilient Ensemble Learning using Evidence Accumulation Clustering G. Candel D. Naccache 10 1 0 18 Oct 2021
Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization Eva Bartz Martin Zaefferer Olaf Mersmann Thomas Bartz-Beielstein 69 4 0 19 Jul 2021
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges B. Bischl Martin Binder Michel Lang Tobias Pielok Jakob Richter ... Theresa Ullmann Marc Becker A. Boulesteix Difan Deng Marius Lindauer 252 514 0 13 Jul 2021
A Dataset-Level Geometric Framework for Ensemble Classifiers Shengli Wu Weimin Ding 15 2 0 16 Jun 2021
AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data F. Xie Yilin Ning Han Yuan B. Goldstein M. Ong Nan Liu B. Chakraborty 64 16 0 13 Jun 2021
Meta-Learning for Symbolic Hyperparameter Defaults Pieter Gijsbers Florian Pfisterer Jan N. van Rijn B. Bischl Joaquin Vanschoren 71 9 0 10 Jun 2021
Inducing a hierarchy for multi-class classification problems Hayden S. Helm Weiwei Yang Sujeeth Bharadwaj Kate Lytvynets Oriana Riva Christopher M. White Ali Geisa Carey E. Priebe 51 7 0 20 Feb 2021
Two-Step Meta-Learning for Time-Series Forecasting Ensemble E. Vaičiukynas Paulius Danėnas Vilius Kontrimas Rimantas Butleris AI4TS 64 9 0 20 Nov 2020
Genetic Programming is Naturally Suited to Evolve Bagging Ensembles M. Virgolin 76 0 0 13 Sep 2020
Joints in Random Forests Alvaro H. C. Correia Robert Peharz Cassio de Campos TPM 78 33 0 25 Jun 2020
The value of text for small business default prediction: A deep learning approach Matthew Stevenson Christophe Mues Cristián Bravo 104 80 0 19 Mar 2020
Collaborative Training of Balanced Random Forests for Open Set Domain Adaptation Jongbin Ryu Jiun Bae Jongwoo Lim 8 3 0 10 Feb 2020
Randomization as Regularization: A Degrees of Freedom Explanation for Random Forest Success L. Mentch Siyu Zhou 87 72 0 01 Nov 2019
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms M. Virgolin Ziyuan Wang Tanja Alderliesten Peter A. N. Bosman 24 2 0 09 Sep 2019
Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting Miles E. Lopes Suofei Wu Thomas C. M. Lee 43 5 0 04 Aug 2019
Automated Machine Learning: State-of-The-Art and Open Challenges Radwa El Shawi Mohamed Maher Sherif Sakr 58 162 0 05 Jun 2019
Best-scored Random Forest Classification H. Hang Xiaoyu Liu Ingo Steinwart 29 2 0 27 May 2019
Continuous-Time Birth-Death MCMC for Bayesian Regression Tree Models Reza Mohammadi M. Pratola M. Kaptein 44 6 0 19 Apr 2019
Hyperparameters and Tuning Strategies for Random Forest Philipp Probst Marvin N. Wright A. Boulesteix 168 1,425 0 10 Apr 2018
OpenML: An R Package to Connect to the Machine Learning Platform OpenML Giuseppe Casalicchio Jakob Bossek Michel Lang Dominik Kirchhoff P. Kerschke B. Hofner H. Seibold Joaquin Vanschoren B. Bischl VLM LRM 110 57 0 05 Jan 2017
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R Marvin N. Wright A. Ziegler 318 2,820 0 18 Aug 2015
OpenML: networked science in machine learning Joaquin Vanschoren Jan N. van Rijn B. Bischl Luís Torgo FedML AI4CE 193 1,335 0 29 Jul 2014