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Understanding Random Forests: From Theory to Practice

28 July 2014

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

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Title
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 Chi Zhao Jing Liu Elena Parilina FAtt 295 6 0 29 Jun 2024
Regression Trees Know Calculus Nathan Wycoff 85 0 0 22 May 2024
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 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 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 Haoze Wu Christopher Hahn Florian Lonsing Makai Mann R. Ramanujan Clark W. Barrett OffRL LRM 94 1 0 18 May 2023
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 Riza Velioglu Jan Philip Göpfert André Artelt Barbara Hammer AI4TS 31 4 0 01 Dec 2022
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 Wouter Haverals M. Kestemont 29 4 0 25 Oct 2022
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? 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 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 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 Jiahua Rao Shuangjia Zheng Yuedong Yang 106 48 0 01 Jul 2021
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 Clément Bénard Gérard Biau Sébastien Da Veiga Erwan Scornet FAtt 100 32 0 25 May 2021
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 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 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 Irving Gómez-Méndez Émilien Joly 73 2 0 10 Nov 2020
Nonparametric Variable Screening with Optimal Decision Stumps Jason M. Klusowski Peter M. Tian 69 4 0 05 Nov 2020
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 David J Armstrong Jevgenij Gamper Theodoros Damoulas 52 27 0 24 Aug 2020
To Bag is to Prune Philippe Goulet Coulombe UQCV 54 9 0 17 Aug 2020
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 Bruna D. Wundervald Andrew C. Parnell Katarina Domijan 63 6 0 12 Jun 2020
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 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 Lorenz Braun S. Nikas Chen Song Vincent Heuveline Holger Fröning 49 39 0 20 Jan 2020
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 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 Pedro M. Milani Julia Ling J. Eaton AI4CE 45 20 0 07 Oct 2019
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 Xiao Li Yu Wang Sumanta Basu Karl Kumbier Bin Yu 231 86 0 26 Jun 2019
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 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 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 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 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 Pallav Kumar Bera R. Kumar Can Isik 52 6 0 12 Nov 2018
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 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 Arnaud Joly 60 10 0 26 Apr 2017
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 Torsten Hothorn A. Zeileis TPM 68 31 0 09 Jan 2017
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 Arnaud Dapogny Kévin Bailly Séverine Dubuisson CVBM 50 42 0 21 Jul 2016
Canonical Correlation Forests Tom Rainforth Frank Wood 91 86 0 20 Jul 2015