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1407.7502
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Understanding Random Forests: From Theory to Practice
28 July 2014
Gilles Louppe
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Papers citing
"Understanding Random Forests: From Theory to Practice"
50 / 51 papers shown
Title
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QUANT: A Minimalist Interval Method for Time Series Classification
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Lightweight Online Learning for Sets of Related Problems in Automated Reasoning
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Lena Krieg
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02 Mar 2023
Explainable Artificial Intelligence for Improved Modeling of Processes
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André Artelt
Barbara Hammer
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31
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Ground Truth Inference for Weakly Supervised Entity Matching
Renzhi Wu
Alexander Bendeck
Xu Chu
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66
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From exemplar to copy: the scribal appropriation of a Hadewijch manuscript computationally explored
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A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic
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13 Apr 2022
Explainable Artificial Intelligence for Pharmacovigilance: What Features Are Important When Predicting Adverse Outcomes?
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A Novel Tropical Geometry-based Interpretable Machine Learning Method: Application in Prognosis of Advanced Heart Failure
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Experimental Investigation and Evaluation of Model-based Hyperparameter Optimization
Eva Bartz
Martin Zaefferer
Olaf Mersmann
Thomas Bartz-Beielstein
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Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction
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Yuedong Yang
106
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Classification algorithms applied to structure formation simulations
Jazhiel Chacón
J. A. Vázquez
E. Almaraz
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SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
Clément Bénard
Gérard Biau
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25 May 2021
Algorithm-Agnostic Explainability for Unsupervised Clustering
Charles A. Ellis
M. Sendi
Eloy P. T. Geenjaar
Sergey Plis
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Vince D. Calhoun
67
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Machine learning-assisted surrogate construction for full-core fuel performance analysis
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44
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MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA
Clément Bénard
Sébastien Da Veiga
Erwan Scornet
132
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On the Consistency of a Random Forest Algorithm in the Presence of Missing Entries
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73
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Nonparametric Variable Screening with Optimal Decision Stumps
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Exoplanet Validation with Machine Learning: 50 new validated Kepler planets
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Jevgenij Gamper
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To Bag is to Prune
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Towards Robust Classification with Deep Generative Forests
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Robert Peharz
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Generalizing Gain Penalization for Feature Selection in Tree-based Models
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61
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12 Jun 2020
Interpretable Random Forests via Rule Extraction
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47
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Isolation Mondrian Forest for Batch and Online Anomaly Detection
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Benyamin Ghojogh
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Mark Crowley
69
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08 Mar 2020
A Simple Model for Portable and Fast Prediction of Execution Time and Power Consumption of GPU Kernels
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49
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20 Jan 2020
Random Forest as a Tumour Genetic Marker Extractor
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D. Torrents
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Orchestrating the Development Lifecycle of Machine Learning-Based IoT Applications: A Taxonomy and Survey
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Generalization of machine-learned turbulent heat flux models applied to film cooling flows
Pedro M. Milani
Julia Ling
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Silas: High Performance, Explainable and Verifiable Machine Learning
Hadrien Bride
Zhe Hou
Jie Dong
J. Dong
Seyedali Mirjalili
50
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03 Oct 2019
A Debiased MDI Feature Importance Measure for Random Forests
Xiao Li
Yu Wang
Sumanta Basu
Karl Kumbier
Bin Yu
231
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26 Jun 2019
AMF: Aggregated Mondrian Forests for Online Learning
Jaouad Mourtada
Stéphane Gaïffas
Erwan Scornet
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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
106
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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
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Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery
B. Kailkhura
Brian Gallagher
Sookyung Kim
A. Hiszpanski
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Bioinformatics Computational Cluster Batch Task Profiling with Machine Learning for Failure Prediction
Christopher Harrison
Christine R. Kirkpatrick
I. Dutra
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Identification of Internal Faults in Indirect Symmetrical Phase Shift Transformers Using Ensemble Learning
Pallav Kumar Bera
R. Kumar
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50
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A Supervised Learning Approach For Heading Detection
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Vijay K. Mago
31
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31 Aug 2018
A high-bias, low-variance introduction to Machine Learning for physicists
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A. G. Day
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133
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Enabling Smart Data: Noise filtering in Big Data classification
Diego García-Gil
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Transformation Forests
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A. Zeileis
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One Class Splitting Criteria for Random Forests
Nicolas Goix
Nicolas Drougard
Romain Brault
Maël Chiapino
63
18
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Dynamic Pose-Robust Facial Expression Recognition by Multi-View Pairwise Conditional Random Forests
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Kévin Bailly
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48
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Canonical Correlation Forests
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89
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