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

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

16 May 2017
Philipp Probst
A. Boulesteix
ArXiv (abs)PDFHTML

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?
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?
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
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
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
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?
Are Ensembles Getting Better all the Time?
Pierre-Alexandre Mattei
Damien Garreau
OODFedML
121
1
0
29 Nov 2023
Linear time Evidence Accumulation Clustering with KMeans
Linear time Evidence Accumulation Clustering with KMeans
G. Candel
18
0
0
15 Nov 2023
The theoretical limits of biometry
The theoretical limits of biometry
G. Candel
CVBM
17
0
0
06 Nov 2023
Does it pay to optimize AUC?
Does it pay to optimize AUC?
Baojian Zhou
Steven Skiena
88
0
0
02 Jun 2023
Heterogeneous Oblique Double Random Forest
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
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
Distributional Adaptive Soft Regression Trees
Nikolaus Umlauf
Nadja Klein
33
1
0
19 Oct 2022
Adaptive deep learning for nonlinear time series models
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
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
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
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
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
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
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
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
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
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
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
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
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
Meta-Learning for Symbolic Hyperparameter Defaults
Pieter Gijsbers
Florian Pfisterer
Jan N. van Rijn
B. Bischl
Joaquin Vanschoren
65
9
0
10 Jun 2021
Inducing a hierarchy for multi-class classification problems
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
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
Genetic Programming is Naturally Suited to Evolve Bagging Ensembles
M. Virgolin
76
0
0
13 Sep 2020
Joints in Random Forests
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
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
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
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
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
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
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
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
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
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
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
VLMLRM
110
57
0
05 Jan 2017
ranger: A Fast Implementation of Random Forests for High Dimensional
  Data in C++ and R
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
OpenML: networked science in machine learning
Joaquin Vanschoren
Jan N. van Rijn
B. Bischl
Luís Torgo
FedMLAI4CE
193
1,335
0
29 Jul 2014
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