On the public citation graph
Unbiased Measurement of Feature Importance in Tree-Based Methods
0 signed · 95 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s11222-016-9646-1openalex-snapshot
Correlation and variable importance in random forests
inferredcites →https://doi.org/10.1016/b978-1-55860-307-3.50037-xopenalex-snapshot
Combining Instance-Based and Model-Based Learning
inferredcites →https://doi.org/10.1080/01621459.2017.1319839openalex-snapshot
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
inferredcites →https://doi.org/10.1093/bib/bbr016openalex-snapshot
Letter to the Editor: On the stability and ranking of predictors from random forest variable importance measures
inferredcites →https://doi.org/10.1093/bib/bbr053openalex-snapshot
Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations
inferredcites →https://doi.org/10.1093/bioinformatics/bty373openalex-snapshot
The revival of the Gini importance?
inferredcites →https://doi.org/10.1109/tnnls.2017.2729778openalex-snapshot
A Novel Consistent Random Forest Framework: Bernoulli Random Forests
inferredcites →https://doi.org/10.1111/insr.12016openalex-snapshot
Fifty Years of Classification and Regression Trees
inferredcites →https://doi.org/10.1177/002224378101800318openalex-snapshot
Book Review: Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
inferredcites →https://doi.org/10.1186/1471-2105-10-213openalex-snapshot
A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data
inferredcites →https://doi.org/10.1186/1471-2105-5-132openalex-snapshot
Simple statistical models predict C-to-U edited sites in plant mitochondrial RNA
inferredcites →https://doi.org/10.1186/1471-2105-7-3openalex-snapshot
Gene selection and classification of microarray data using random forest
inferredcites →https://doi.org/10.1186/1471-2105-8-25openalex-snapshot
Bias in random forest variable importance measures: Illustrations, sources and a solution
inferredcites →https://doi.org/10.1186/1471-2105-9-307openalex-snapshot
Conditional variable importance for random forests
inferredcites →https://doi.org/10.1198/016214501753168271openalex-snapshot
Classification Trees With Unbiased Multiway Splits
inferredcites →https://doi.org/10.1198/106186006x133933openalex-snapshot
Unbiased Recursive Partitioning: A Conditional Inference Framework
inferredcites →https://doi.org/10.1198/106186007x237892openalex-snapshot
Generalized Functional ANOVA Diagnostics for High-Dimensional Functions of Dependent Variables
inferredcites →https://doi.org/10.1198/106186008x344522openalex-snapshot
A Bias Correction Algorithm for the Gini Variable Importance Measure in Classification Trees
inferredcites →https://doi.org/10.1214/07-ejs039openalex-snapshot
Variable importance in binary regression trees and forests
inferredcites →https://doi.org/10.1214/09-aoas260openalex-snapshot
Improving the precision of classification trees
inferredcites →https://doi.org/10.1214/15-aos1337openalex-snapshot
Controlling the false discovery rate via knockoffs
inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
Greedy function approximation: A gradient boosting machine.
inferredcites →https://doi.org/10.2307/3150985openalex-snapshot
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
inferredcites →https://doi.org/10.32614/cran.package.partyopenalex-snapshot
party: A Laboratory for Recursive Partytioning
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.1906.10845openalex-snapshot
A Debiased MDI Feature Importance Measure for Random Forests
inferredcites →https://doi.org/10.5555/2946645.2946671openalex-snapshot
Quantifying uncertainty in random forests via confidence intervals and hypothesis tests
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4860194openalex-extracted
Identifying Ideal Turbine Locations Using Explainable Ai Techniques
inferred← citeshttps://doi.org/10.1007/s10115-025-02616-xopenalex-snapshot
Iterative feature exclusion ranking for deep tabular learning
inferred← citeshttps://doi.org/10.1007/s11116-021-10250-zopenalex-snapshot
Modeling household online shopping demand in the U.S.: a machine learning approach and comparative investigation between 2009 and 2017
inferred← citeshttps://doi.org/10.1007/s13369-025-10090-4openalex-snapshot
Named Entity Recognition Based Neural Network Framework for Stock Trend Prediction Using Latent Dirichlet Allocation
inferred← citeshttps://doi.org/10.1007/s42947-025-00653-xopenalex-snapshot
Resilient Modulus Prediction for Fine-Grained Soils Using a Novel Voting-Based Ensemble Approach: Integrating Gradient Boosting and Multilayer Perceptron Neural Networks
inferred← citeshttps://doi.org/10.1007/s43503-024-00047-1openalex-snapshot
Estimation of rock strength parameters from petrological contents using tree-based machine learning techniques
inferred← citeshttps://doi.org/10.1016/j.apgeog.2023.102928openalex-snapshot
Effectiveness variation of different census outreach activities: An empirical analysis from the state of Illinois using machine learning and user interface technologies for participatory data collection
inferred← citeshttps://doi.org/10.1016/j.buildenv.2023.110047openalex-snapshot
Alert-based wearable sensing system for individualized thermal preference prediction
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.107284openalex-snapshot
Signal detection and material identification method for loose particles inside sealed relays based on fusion classification model
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.131640openalex-snapshot
Modeling social unrest: The geographical influence on social unrest prediction
inferred← citeshttps://doi.org/10.1016/j.heliyon.2023.e19422openalex-snapshot
Single-label machine learning classification revealed some hidden but inter-related causes of five psychotic disorder diseases
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2022.06.015openalex-snapshot
Characterising retrieval uncertainty of chlorophyll-a algorithms in oligotrophic and mesotrophic lakes and reservoirs
inferred← citeshttps://doi.org/10.1016/j.jag.2021.102595openalex-snapshot
Developing a multi-classifier system to classify OSM tags based on centrality parameters
inferred← citeshttps://doi.org/10.1016/j.still.2025.106603openalex-snapshot
Exploring and predicting nitrogen fertilizer use efficiency of maize (Zea mays L.)-soybean (Glycine max (L.) Merr.) intercropping systems in China: A combined Meta-analysis and machine learning approach
inferred← citeshttps://doi.org/10.1016/j.susmat.2021.e00381openalex-snapshot
Sensitivity analysis of coating mortars according to their specific heat, specific gravity, thermal conductivity, and thickness in contribution to the global thermal performance of buildings
inferred← citeshttps://doi.org/10.1029/2024ef004540openalex-snapshot
How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences
inferred← citeshttps://doi.org/10.1038/s41598-024-79036-4openalex-snapshot
SNPs and blood inflammatory marker featured machine learning for predicting the efficacy of fluorouracil-based chemotherapy in colorectal cancer
inferred← citeshttps://doi.org/10.1063/5.0210219openalex-snapshot
The prediction of hypercholesterolemia as a risk factor of cardiac disease using machine learning models
inferred← citeshttps://doi.org/10.1073/pnas.2118636119openalex-snapshot
Provable Boolean interaction recovery from tree ensemble obtained via random forests
inferred← citeshttps://doi.org/10.1073/pnas.2310151122openalex-snapshot
Fast Interpretable Greedy-Tree Sums
inferred← citeshttps://doi.org/10.1080/03610926.2020.1764042openalex-snapshot
Unbiased variable importance for random forests
inferred← citeshttps://doi.org/10.1080/10618600.2020.1820345openalex-snapshot
Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and Its Variance Estimate
inferred← citeshttps://doi.org/10.1093/biomet/asac017openalex-snapshot
Mean decrease accuracy for random forests: inconsistency, and a practical solution via the Sobol-MDA
inferred← citeshttps://doi.org/10.1093/mnras/stab1120openalex-snapshot
Hybrid analytic and machine-learned baryonic property insertion into galactic dark matter haloes
inferred← citeshttps://doi.org/10.1108/jeim-09-2025-0938openalex-snapshot
Predicting the patient’s remaining length of stay for real-time decision-making: a process mining approach
inferred← citeshttps://doi.org/10.1109/access.2025.3567140openalex-snapshot
Understanding Software Defect Prediction Through eXplainable Neural Additive Models
inferred← citeshttps://doi.org/10.1109/access.2025.3638612openalex-snapshot
Automated Feature Engineering Based on Explainable Artificial Intelligence for Time Series Forecasting
inferred← citeshttps://doi.org/10.1109/access.2025.3649636openalex-snapshot
A Novel Hybrid Approach for Identification of Discriminative Features in Phishing Emails
inferred← citeshttps://doi.org/10.1109/access.2026.3656717openalex-snapshot
Stock Crash Risk Prediction With Implied Volatility Index: A Comparison of Tree-Based and Transformer-Based Models
inferred← citeshttps://doi.org/10.1109/cac67268.2025.11486853openalex-snapshot
Multi-Round UAVs Combat Maneuver Decision Game Based on MV-LightGBM Algorithm
inferred← citeshttps://doi.org/10.1109/cbms65348.2025.00127openalex-snapshot
Classifying Residual Inhibition in the Context of Tinnitus: An Interpretable Machine Learning Approach
inferred← citeshttps://doi.org/10.1109/deeptest66595.2025.00006openalex-snapshot
Improving the Reliability of Failure Prediction Models through Concept Drift Monitoring
inferred← citeshttps://doi.org/10.1109/iccc52777.2021.9580225openalex-snapshot
Edge Intelligence Enabled Soft Decentralized Authentication in UAV Swarm
inferred← citeshttps://doi.org/10.1109/icpr56361.2022.9956124openalex-snapshot
A Novel Splitting Criterion Inspired by Geometric Mean Metric Learning for Decision Tree
inferred← citeshttps://doi.org/10.1109/qrs-c63300.2024.00079openalex-snapshot
A Model-Agnostic Interpretability Approach Based on Enhanced Hierarchical Clustering
inferred← citeshttps://doi.org/10.1139/cjfas-2023-0197openalex-snapshot
Identifying optimal variables for machine-learning-based fish distribution modeling
inferred← citeshttps://doi.org/10.1145/3714394.3756206openalex-snapshot
Evaluating Rhythmic Representations in Mental Health from Wearable Devices Using the GLOBEM Datasets
inferred← citeshttps://doi.org/10.1155/je/6435980openalex-snapshot
Thermal Environment Effect on Machine Tool Ball Screw Based on Experimental Investigation and Numerical Simulation via Machine Learning Prediction
inferred← citeshttps://doi.org/10.11606/d.55.2022.tde-16122022-180337openalex-snapshot
Técnicas de interpretabilidade para aprendizado de máquina: um estudo abordando avaliação de crédito e detecção de fraude
inferred← citeshttps://doi.org/10.1214/21-aihp1240openalex-snapshot
Trees, forests, and impurity-based variable importance in regression
inferred← citeshttps://doi.org/10.1353/obs.2021.0027openalex-snapshot
Bridging Breiman's Brook: From Algorithmic Modeling to Statistical Learning
inferred← citeshttps://doi.org/10.1590/s1983-41952022000500003openalex-snapshot
Comparison of machine learning techniques to predict the compressive strength of concrete and considerations on model generalization
inferred← citeshttps://doi.org/10.1609/aaai.v36i8.20810openalex-snapshot
Feature Importance Explanations for Temporal Black-Box Models
inferred← citeshttps://doi.org/10.2139/ssrn.5891309openalex-snapshot
Unraveling the Determinants of Urban Energy Intensity in China: An XGBoost-SHAP Analysis of 286 Cities
inferred← citeshttps://doi.org/10.2139/ssrn.6996724openalex-snapshot
Hybrid mechanistic–machine learning framework for cross-site prediction of root-zone soil water depletion in agricultural water management systems
inferred← citeshttps://doi.org/10.24963/ijcai.2023/515openalex-snapshot
Unbiased Gradient Boosting Decision Tree with Unbiased Feature Importance
inferred← citeshttps://doi.org/10.26555/ijain.v9i3.1008openalex-snapshot
Evaluation of sleep stage classification using feature importance of EEG signal for big data healthcare
inferred← citeshttps://doi.org/10.32604/cmes.2022.021165openalex-snapshot
Rock Strength Estimation Using Several Tree-Based ML Techniques
inferred← citeshttps://doi.org/10.3389/fenrg.2023.1250336openalex-snapshot
Analysis of sensitive factors for sidetrack drilling in water-flooded oil reservoirs: data mining based on actual field data
inferred← citeshttps://doi.org/10.3390/en15124288openalex-snapshot
Applying Machine Learning to Predict the Rate of Penetration for Geothermal Drilling Located in the Utah FORGE Site
inferred← citeshttps://doi.org/10.3390/urbansci9040088openalex-snapshot
Analyzing Citizens’ Perception and Attitudes Towards Housing Development in Norwalk Through SEM and Machine Learning Methods
inferred← citeshttps://doi.org/10.4018/jdm.322097openalex-snapshot
Incorporating I Ching Knowledge Into Prediction Task via Data Mining
inferred← citeshttps://doi.org/10.48550/arxiv.2001.04295openalex-snapshot
Trees, forests, and impurity-based variable importance
inferred← citeshttps://doi.org/10.48550/arxiv.2003.12043openalex-snapshot
From unbiased MDI Feature Importance to Explainable AI for Trees
inferred← citeshttps://doi.org/10.48550/arxiv.2102.12328openalex-snapshot
Bridging Breiman's Brook: From Algorithmic Modeling to Statistical Learning
inferred← citeshttps://doi.org/10.52058/2786-6025-2024-7(35)-577-593openalex-snapshot
АНСАМБЛЕВІ МОДЕЛІ ДЕРЕВ ПРИЙНЯТТЯ РІШЕНЬ В ЗАДАЧАХ КЛАСИФІКАЦІЇ
inferred← citeshttps://doi.org/10.5463/thesis.344openalex-snapshot
Turing and Van Gogh walk into a bar
inferred← citeshttps://doi.org/10.60084/mp.v2i2.217openalex-snapshot
Application of Ensemble Machine Learning Methods for QSAR Classification of Leukotriene A4 Hydrolase Inhibitors in Drug Discovery
inferred← citeshttps://doi.org/10.61112/jiens.1555284openalex-snapshot
Yüksek performanslı betonun basınç dayanımının farklı makine öğrenimi algoritmaları ile tahmin edilmesi
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.