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A Bayesian Bradley-Terry model to compare multiple ML algorithms on
  multiple data sets
v1v2 (latest)

A Bayesian Bradley-Terry model to compare multiple ML algorithms on multiple data sets

9 August 2022
Jacques Wainer
ArXiv (abs)PDFHTML

Papers citing "A Bayesian Bradley-Terry model to compare multiple ML algorithms on multiple data sets"

16 / 16 papers shown
Title
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
Shenhao Wang
Baichuan Mo
Stephane Hess
Jinhuan Zhao
Jinhua Zhao
97
26
0
01 Feb 2021
How to tune the RBF SVM hyperparameters?: An empirical evaluation of 18
  search algorithms
How to tune the RBF SVM hyperparameters?: An empirical evaluation of 18 search algorithms
Jacques Wainer
Pablo Fonseca
41
37
0
26 Aug 2020
Evaluation of Text Generation: A Survey
Evaluation of Text Generation: A Survey
Asli Celikyilmaz
Elizabeth Clark
Jianfeng Gao
ELMLM&MA
112
387
0
26 Jun 2020
Convergence diagnostics for Markov chain Monte Carlo
Convergence diagnostics for Markov chain Monte Carlo
Vivekananda Roy
66
219
0
26 Sep 2019
Nested cross-validation when selecting classifiers is overzealous for
  most practical applications
Nested cross-validation when selecting classifiers is overzealous for most practical applications
Jacques Wainer
G. Cawley
32
214
0
25 Sep 2018
OpenML Benchmarking Suites
OpenML Benchmarking Suites
B. Bischl
Giuseppe Casalicchio
Matthias Feurer
Pieter Gijsbers
Frank Hutter
Michel Lang
R. G. Mantovani
Jan N. van Rijn
Joaquin Vanschoren
VLMELM
89
162
0
11 Aug 2017
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and
  Comparison
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison
Randal S. Olson
William La Cava
Patryk Orzechowski
Ryan J. Urbanowicz
J. Moore
407
379
0
01 Mar 2017
Statistical comparison of classifiers through Bayesian hierarchical
  modelling
Statistical comparison of classifiers through Bayesian hierarchical modelling
Giorgio Corani
A. Benavoli
J. Demšar
Francesca Mangili
Marco Zaffalon
41
55
0
28 Sep 2016
Time for a change: a tutorial for comparing multiple classifiers through
  Bayesian analysis
Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis
A. Benavoli
Giorgio Corani
J. Demšar
Marco Zaffalon
BDL
62
424
0
14 Jun 2016
Comparison of 14 different families of classification algorithms on 115
  binary datasets
Comparison of 14 different families of classification algorithms on 115 binary datasets
Jacques Wainer
38
85
0
02 Jun 2016
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
809
39,031
0
09 Mar 2016
Practical Bayesian model evaluation using leave-one-out cross-validation
  and WAIC
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
Aki Vehtari
Andrew Gelman
Jonah Gabry
124
4,055
0
16 Jul 2015
Should we really use post-hoc tests based on mean-ranks?
Should we really use post-hoc tests based on mean-ranks?
A. Benavoli
Giorgio Corani
Francesca Mangili
50
379
0
09 May 2015
Evaluation Measures for Hierarchical Classification: a unified view and
  novel approaches
Evaluation Measures for Hierarchical Classification: a unified view and novel approaches
Aris Kosmopoulos
Ioannis Partalas
Éric Gaussier
George Giannakopoulos
Ion Androutsopoulos
64
189
0
28 Jun 2013
Efficient Bayesian Inference for Generalized Bradley-Terry Models
Efficient Bayesian Inference for Generalized Bradley-Terry Models
François Caron
Arnaud Doucet
155
141
0
08 Nov 2010
Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable
  Information Criterion in Singular Learning Theory
Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory
Sumio Watanabe
129
2,387
0
14 Apr 2010
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