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Understanding Random Forests: From Theory to Practice
v1v2v3 (latest)

Understanding Random Forests: From Theory to Practice

28 July 2014
Gilles Louppe
ArXiv (abs)PDFHTML

Papers citing "Understanding Random Forests: From Theory to Practice"

50 / 51 papers shown
Title
DynFrs: An Efficient Framework for Machine Unlearning in Random Forest
DynFrs: An Efficient Framework for Machine Unlearning in Random Forest
Shurong Wang
Zhuoyang Shen
Xinbao Qiao
Tongning Zhang
Meng Zhang
MU
153
0
0
02 Oct 2024
ShapG: new feature importance method based on the Shapley value
ShapG: new feature importance method based on the Shapley value
Chi Zhao
Jing Liu
Elena Parilina
FAtt
295
6
0
29 Jun 2024
Regression Trees Know Calculus
Regression Trees Know Calculus
Nathan Wycoff
85
0
0
22 May 2024
Sky Imager-Based Forecast of Solar Irradiance Using Machine Learning
Sky Imager-Based Forecast of Solar Irradiance Using Machine Learning
A. Al-lahham
Obaidah Theeb
Khaled Elalem
Tariq A. Alshawi
Saleh A. Alshebeili
39
38
0
26 Oct 2023
BehaVR: User Identification Based on VR Sensor Data
BehaVR: User Identification Based on VR Sensor Data
Ismat Jarin
Yu Duan
R. Trimananda
Hao Cui
Salma Elmalaki
A. Markopoulou
66
4
0
14 Aug 2023
QUANT: A Minimalist Interval Method for Time Series Classification
QUANT: A Minimalist Interval Method for Time Series Classification
Angus Dempster
Daniel F. Schmidt
Geoffrey I. Webb
AI4TS
61
9
0
02 Aug 2023
Lightweight Online Learning for Sets of Related Problems in Automated
  Reasoning
Lightweight Online Learning for Sets of Related Problems in Automated Reasoning
Haoze Wu
Christopher Hahn
Florian Lonsing
Makai Mann
R. Ramanujan
Clark W. Barrett
OffRLLRM
94
1
0
18 May 2023
A Notion of Feature Importance by Decorrelation and Detection of Trends
  by Random Forest Regression
A Notion of Feature Importance by Decorrelation and Detection of Trends by Random Forest Regression
Yannick Gerstorfer
Lena Krieg
Max Hahn-Klimroth
44
7
0
02 Mar 2023
Explainable Artificial Intelligence for Improved Modeling of Processes
Explainable Artificial Intelligence for Improved Modeling of Processes
Riza Velioglu
Jan Philip Göpfert
André Artelt
Barbara Hammer
AI4TS
31
4
0
01 Dec 2022
Ground Truth Inference for Weakly Supervised Entity Matching
Ground Truth Inference for Weakly Supervised Entity Matching
Renzhi Wu
Alexander Bendeck
Xu Chu
Yeye He
66
8
0
13 Nov 2022
From exemplar to copy: the scribal appropriation of a Hadewijch
  manuscript computationally explored
From exemplar to copy: the scribal appropriation of a Hadewijch manuscript computationally explored
Wouter Haverals
M. Kestemont
29
4
0
25 Oct 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and
  Vibroacoustic
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic
Barbara Z Cunha
C. Droz
A. Zine
Stéphane Foulard
M. Ichchou
AI4CE
71
91
0
13 Apr 2022
Explainable Artificial Intelligence for Pharmacovigilance: What Features
  Are Important When Predicting Adverse Outcomes?
Explainable Artificial Intelligence for Pharmacovigilance: What Features Are Important When Predicting Adverse Outcomes?
I. Ward
Ling Wang
Juan Lu
M. Bennamoun
Girish Dwivedi
Frank M. Sanfilippo
151
35
0
25 Dec 2021
A Novel Tropical Geometry-based Interpretable Machine Learning Method:
  Application in Prognosis of Advanced Heart Failure
A Novel Tropical Geometry-based Interpretable Machine Learning Method: Application in Prognosis of Advanced Heart Failure
Heming Yao
H. Derksen
J. Golbus
Justin Zhang
K. Aaronson
Jonathan Gryak
Kayvan Najarian
63
4
0
09 Dec 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
Quantitative Evaluation of Explainable Graph Neural Networks for
  Molecular Property Prediction
Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction
Jiahua Rao
Shuangjia Zheng
Yuedong Yang
106
48
0
01 Jul 2021
Classification algorithms applied to structure formation simulations
Classification algorithms applied to structure formation simulations
Jazhiel Chacón
J. A. Vázquez
E. Almaraz
AI4CE
57
7
0
11 Jun 2021
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
Clément Bénard
Gérard Biau
Sébastien Da Veiga
Erwan Scornet
FAtt
100
32
0
25 May 2021
Algorithm-Agnostic Explainability for Unsupervised Clustering
Algorithm-Agnostic Explainability for Unsupervised Clustering
Charles A. Ellis
M. Sendi
Eloy P. T. Geenjaar
Sergey Plis
Robyn L. Miller
Vince D. Calhoun
69
25
0
17 May 2021
Machine learning-assisted surrogate construction for full-core fuel
  performance analysis
Machine learning-assisted surrogate construction for full-core fuel performance analysis
Yifeng Che
J. Yurko
K. Shirvan
46
10
0
17 Apr 2021
MDA for random forests: inconsistency, and a practical solution via the
  Sobol-MDA
MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA
Clément Bénard
Sébastien Da Veiga
Erwan Scornet
132
53
0
26 Feb 2021
On the Consistency of a Random Forest Algorithm in the Presence of
  Missing Entries
On the Consistency of a Random Forest Algorithm in the Presence of Missing Entries
Irving Gómez-Méndez
Émilien Joly
73
2
0
10 Nov 2020
Nonparametric Variable Screening with Optimal Decision Stumps
Nonparametric Variable Screening with Optimal Decision Stumps
Jason M. Klusowski
Peter M. Tian
69
4
0
05 Nov 2020
Out-Of-Bag Anomaly Detection
Out-Of-Bag Anomaly Detection
Egor Klevak
Sangdi Lin
Andrea Martin
O. Linda
Eric K. Ringger
OODD
46
0
0
20 Sep 2020
Exoplanet Validation with Machine Learning: 50 new validated Kepler
  planets
Exoplanet Validation with Machine Learning: 50 new validated Kepler planets
David J Armstrong
Jevgenij Gamper
Theodoros Damoulas
52
27
0
24 Aug 2020
To Bag is to Prune
To Bag is to Prune
Philippe Goulet Coulombe
UQCV
54
9
0
17 Aug 2020
Towards Robust Classification with Deep Generative Forests
Towards Robust Classification with Deep Generative Forests
Alvaro H. C. Correia
Robert Peharz
Cassio de Campos
TPM
27
2
0
11 Jul 2020
Generalizing Gain Penalization for Feature Selection in Tree-based
  Models
Generalizing Gain Penalization for Feature Selection in Tree-based Models
Bruna D. Wundervald
Andrew C. Parnell
Katarina Domijan
63
6
0
12 Jun 2020
Interpretable Random Forests via Rule Extraction
Interpretable Random Forests via Rule Extraction
Clément Bénard
Gérard Biau
Sébastien Da Veiga
Erwan Scornet
47
59
0
29 Apr 2020
Isolation Mondrian Forest for Batch and Online Anomaly Detection
Isolation Mondrian Forest for Batch and Online Anomaly Detection
Haoran Ma
Benyamin Ghojogh
Maria N. Samad
Dongyu Zheng
Mark Crowley
69
27
0
08 Mar 2020
A Simple Model for Portable and Fast Prediction of Execution Time and
  Power Consumption of GPU Kernels
A Simple Model for Portable and Fast Prediction of Execution Time and Power Consumption of GPU Kernels
Lorenz Braun
S. Nikas
Chen Song
Vincent Heuveline
Holger Fröning
49
39
0
20 Jan 2020
Random Forest as a Tumour Genetic Marker Extractor
Random Forest as a Tumour Genetic Marker Extractor
Raquel Pérez-Arnal
Dario Garcia-Gasulla
D. Torrents
Ferran Parés
Ulises Cortés
Jesús Labarta
Eduard Ayguadé
22
0
0
26 Nov 2019
Orchestrating the Development Lifecycle of Machine Learning-Based IoT
  Applications: A Taxonomy and Survey
Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey
Bin Qian
Jie Su
Z. Wen
D. N. Jha
Yinhao Li
...
Albert Y. Zomaya
Omer F. Rana
Lizhe Wang
Maciej Koutny
R. Ranjan
71
4
0
11 Oct 2019
Generalization of machine-learned turbulent heat flux models applied to
  film cooling flows
Generalization of machine-learned turbulent heat flux models applied to film cooling flows
Pedro M. Milani
Julia Ling
J. Eaton
AI4CE
45
20
0
07 Oct 2019
Silas: High Performance, Explainable and Verifiable Machine Learning
Silas: High Performance, Explainable and Verifiable Machine Learning
Hadrien Bride
Zhe Hou
Jie Dong
J. Dong
Seyedali Mirjalili
52
7
0
03 Oct 2019
A Debiased MDI Feature Importance Measure for Random Forests
A Debiased MDI Feature Importance Measure for Random Forests
Xiao Li
Yu Wang
Sumanta Basu
Karl Kumbier
Bin Yu
231
86
0
26 Jun 2019
AMF: Aggregated Mondrian Forests for Online Learning
AMF: Aggregated Mondrian Forests for Online Learning
Jaouad Mourtada
Stéphane Gaïffas
Erwan Scornet
90
29
0
25 Jun 2019
Explainable AI for Trees: From Local Explanations to Global
  Understanding
Explainable AI for Trees: From Local Explanations to Global Understanding
Scott M. Lundberg
G. Erion
Hugh Chen
A. DeGrave
J. Prutkin
B. Nair
R. Katz
J. Himmelfarb
N. Bansal
Su-In Lee
FAtt
108
291
0
11 May 2019
ATMSeer: Increasing Transparency and Controllability in Automated
  Machine Learning
ATMSeer: Increasing Transparency and Controllability in Automated Machine Learning
Qianwen Wang
Yao Ming
Zhihua Jin
Qiaomu Shen
Dongyu Liu
Micah J. Smith
K. Veeramachaneni
Huamin Qu
HAI
65
101
0
13 Feb 2019
Reliable and Explainable Machine Learning Methods for Accelerated
  Material Discovery
Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery
B. Kailkhura
Brian Gallagher
Sookyung Kim
A. Hiszpanski
T. Y. Han
79
155
0
05 Jan 2019
Bioinformatics Computational Cluster Batch Task Profiling with Machine
  Learning for Failure Prediction
Bioinformatics Computational Cluster Batch Task Profiling with Machine Learning for Failure Prediction
Christopher Harrison
Christine R. Kirkpatrick
I. Dutra
22
1
0
22 Dec 2018
Identification of Internal Faults in Indirect Symmetrical Phase Shift
  Transformers Using Ensemble Learning
Identification of Internal Faults in Indirect Symmetrical Phase Shift Transformers Using Ensemble Learning
Pallav Kumar Bera
R. Kumar
Can Isik
52
6
0
12 Nov 2018
A Supervised Learning Approach For Heading Detection
A Supervised Learning Approach For Heading Detection
S. Budhiraja
Vijay K. Mago
33
12
0
31 Aug 2018
A high-bias, low-variance introduction to Machine Learning for
  physicists
A high-bias, low-variance introduction to Machine Learning for physicists
Pankaj Mehta
Marin Bukov
Ching-Hao Wang
A. G. Day
C. Richardson
Charles K. Fisher
D. Schwab
AI4CE
133
884
0
23 Mar 2018
Exploiting random projections and sparsity with random forests and
  gradient boosting methods -- Application to multi-label and multi-output
  learning, random forest model compression and leveraging input sparsity
Exploiting random projections and sparsity with random forests and gradient boosting methods -- Application to multi-label and multi-output learning, random forest model compression and leveraging input sparsity
Arnaud Joly
60
10
0
26 Apr 2017
Enabling Smart Data: Noise filtering in Big Data classification
Enabling Smart Data: Noise filtering in Big Data classification
Diego García-Gil
Julián Luengo
S. García
Francisco Herrera
101
143
0
06 Apr 2017
Transformation Forests
Transformation Forests
Torsten Hothorn
A. Zeileis
TPM
68
31
0
09 Jan 2017
One Class Splitting Criteria for Random Forests
One Class Splitting Criteria for Random Forests
Nicolas Goix
Nicolas Drougard
Romain Brault
Maël Chiapino
63
18
0
07 Nov 2016
Dynamic Pose-Robust Facial Expression Recognition by Multi-View Pairwise
  Conditional Random Forests
Dynamic Pose-Robust Facial Expression Recognition by Multi-View Pairwise Conditional Random Forests
Arnaud Dapogny
Kévin Bailly
Séverine Dubuisson
CVBM
50
42
0
21 Jul 2016
Canonical Correlation Forests
Canonical Correlation Forests
Tom Rainforth
Frank Wood
91
86
0
20 Jul 2015
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