Search Results

Model economic phenomena with CART and Random Forest algorithms,
Benjamin David, from University of Paris Nanterre, EconomiX (2017)
Keywords: decision trees, CART, Random Forest

Electric Power Forecasting in Inner Mongolia by Random Forest,
Zhi-jun Wei, from Springer (2013)
Keywords: Forecasting, Power demand, Random Forest

Random Forest as a Model for Czech Forecasting,
Katerina Gawthorpe, in Prague Economic Papers (2021)
Keywords: Random forest, Czech Republic, forecast, regression tree

Comments on: A random forest guided tour,
Giles Hooker and Lucas Mentch, in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research (2016)
Keywords: Random forests, Machine learning, Extrapolation, Variable importance

On the asymptotics of random forests,
Erwan Scornet, in Journal of Multivariate Analysis (2016)
Keywords: Random forests; Randomization; Consistency; Central limit theorem; Empirical process; Number of trees; q-quantile;

Comments on: A random forest guided tour,
Sylvain Arlot and Robin Genuer, in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research (2016)
Keywords: Random forests, Estimation error, Approximation error, Subagging, Bagging, Hold-out random forests

DIAGNOSING ASSETS IMPAIRMENT BY USING RANDOM FORESTS MODEL,
Ching-Lung Chen and Chei-Wei Wu, in International Journal of Information Technology & Decision Making (IJITDM) (2012)
Keywords: Assets impairment, random forests, diagnosis, logit regression

A Random Forest approach of the Evolution of Inequality of Opportunity in Mexico,
Thibaut Plassot, Isidro Soloaga and Pedro J. Torres, from ECINEQ, Society for the Study of Economic Inequality (2022)
Keywords: Inequality Of Opportunity, Mexico, Shapley Decomposition, Random Forests

Targeting predictors in random forest regression,
Daniel Borup, Bent Jesper Christensen, Nicolaj N. Mühlbach and Mikkel S. Nielsen, from Department of Economics and Business Economics, Aarhus University (2020)
Keywords: Random forests, LASSO, high-dimensional forecasting, weak predictors, targeted predictors

Medoid splits for efficient random forests in metric spaces,
Matthieu Bulté and Helle Sørensen, in Computational Statistics & Data Analysis (2024)
Keywords: Least squares regression; Medoid; Metric spaces; Random forest; Random objects;

Mixed random forest, cointegration, and forecasting gasoline prices,
Alvaro Escribano and Dandan Wang, in International Journal of Forecasting (2021)
Keywords: Oil prices; Rockets and feathers; Cointegration; Nonlinear error correction; Machine learning; Random forest; Mixed random forest;

Clasificación de la Pobreza en Bolivia, Utilizando Random Forest y XGBoost,
Cristian Paucara, in Cuadernos de Investigación Económica Boliviana (2022)
Keywords: Pobreza, random forest, XGBoost, Bolivia

Using random forests to estimate win probability before each play of an NFL game,
Lock Dennis and Nettleton Dan, in Journal of Quantitative Analysis in Sports (2014)
Keywords: random forest, NFL, win probability

Spatiotemporal Dynamic Changes and Prediction of Wild Fruit Forests in Emin County, Xinjiang, China, Based on Random Forest and PLUS Model,
Qian Sun, Liang Guo, Guizhen Gao, Xinyue Hu, Tingwei Song and Jinyi Huang, in Sustainability (2024)
Keywords: wild fruit forest; random forest algorithm; spatiotemporal distribution; overgrazing; tourism

Performance Evaluation of the GIS-Based Data-Mining Techniques Decision Tree, Random Forest, and Rotation Forest for Landslide Susceptibility Modeling,
Soyoung Park, Se-Yeong Hamm and Jinsoo Kim, in Sustainability (2019)
Keywords: decision tree; ensemble learning; landslide susceptibility; random forest; rotation forest

Forest fire mapping: a comparison between GIS-based random forest and Bayesian models,
Farzaneh Noroozi, Gholamabbas Ghanbarian, Roja Safaeian and Hamid Reza Pourghasemi, in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards (2024)
Keywords: Random forest, Bayesian approach, Forest fire, GIS, Prioritization

A Mandarin Tone Recognition Algorithm Based on Random Forest and Feature Fusion †,
Jiameng Yan, Qiang Meng, Lan Tian, Xiaoyu Wang, Junhui Liu, Meng Li, Ming Zeng and Huifang Xu, in Mathematics (2023)
Keywords: tone recognition; random forest; feature fusion; Mandarin

Inflation and Inflation Uncertainty in Growth Model of Barro: An Application of Random Forest Method,
Houcine Senoussi, in International Econometric Review (IER) (2021)
Keywords: Growth, Inflation, Machine Learning, Random Forest

Identification of nonlinear determinants of stock indices derived by Random Forest algorithm,
Tratkowski Grzegorz, in International Journal of Management and Economics (2020)
Keywords: determinants, Random Forest, stock index, machine learning

Analysis of Random Forest Modeling Strategies for Multi-Step Wind Speed Forecasting,
Daniel Vassallo, Raghavendra Krishnamurthy, Thomas Sherman and Harindra J. S. Fernando, in Energies (2020)
Keywords: wind speed forecasting; machine learning; random forest

Influence Analysis and Prediction of ESDD and NSDD Based on Random Forests,
Ang Ren, Qingquan Li and Huaishuo Xiao, in Energies (2017)
Keywords: insulators; ESDD; NSDD; random forests; mutual information

Using Smart Persistence and Random Forests to Predict Photovoltaic Energy Production,
Javier Huertas Tato and Miguel Centeno Brito, in Energies (2018)
Keywords: smart persistence; photovoltaic forecasting; random forests

A bias-variance analysis of state-of-the-art random forest text classifiers,
Thiago Salles, Leonardo Rocha and Marcos Gonçalves, in Advances in Data Analysis and Classification (2021)
Keywords: Random forests, Text classification, Bias variance analysis

Models under which random forests perform badly; consequences for applications,
José A. Ferreira, in Computational Statistics (2022)
Keywords: Statistical prediction, Random forests, Convergence, Consistency

Random forests-based early warning system for bank failures,
Katsuyuki Tanaka, Takuji Kinkyo and Shigeyuki Hamori, in Economics Letters (2016)
Keywords: Random forests; Early warning system; Bank failure;

Research on SMEs Credit Risk Prediction Based on Decision Tree and Random Forest,
Lei Han, Qixin Bo, Guiying Wei and Yingxue Pan, from Springer (2024)
Keywords: SMEs, Credit risk, decision tree, random forest

Research on Quantitative Stock Selection Method Based on Random Forest,
Haining Yang and Xuedong Gao, from Springer (2021)
Keywords: Decision tree, Random forest, Quantitative stock selection

Predicting Customer Retention and Profitability by Using Random Forests and Regression Forests Techniques,
B. Larivière and Dirk Van den Poel, from Ghent University, Faculty of Economics and Business Administration (2004)
Keywords: Data mining, Customer relationship management, Customer retention and profitability, Random forests and regression forests.

Prediction of disease using fuzzy random forest,
Balaji K. Bodkhe and Sanjay Sood, in International Journal of Intelligent Enterprise (2021)
Keywords: genetic algorithm; fuzzy random forest; FRF; fuzzy clustering algorithms.

A new variable selection approach using Random Forests,
A. Hapfelmeier and K. Ulm, in Computational Statistics & Data Analysis (2013)
Keywords: Random Forests; Variable selection; Permutation tests; Multiple testing;

Automated stock picking using random forests,
Christian Breitung, in Journal of Empirical Finance (2023)
Keywords: Stock picking; Machine learning; Random forest; Portfolio optimization;

Effective Macrosomia Prediction Using Random Forest Algorithm,
Fangyi Wang, Yongchao Wang, Xiaokang Ji and Zhiping Wang, in IJERPH (2022)
Keywords: random forest; macrosomia; interspinal diameter; sacral external diameter; transverse outlet

Random Forest Pruning Techniques: A Recent Review,
Youness Manzali and Mohamed Elfar, in SN Operations Research Forum (2023)
Keywords: Ensemble method, Random forest, Pruning techniques, Tree selection

EU Merger Policy Predictability Using Random Forests,
Pauline Affeldt, from DIW Berlin, German Institute for Economic Research (2019)
Keywords: Merger policy reform, DG Competition, Prediction, Random Forests

Random Forest Estimation of the Ordered Choice Model,
Michael Lechner and Gabriel Okasa, from University of St. Gallen, School of Economics and Political Science (2019)
Keywords: Ordered choice models, random forests, probabilities, marginal effects, machine learning

Determinants of Central Bank Independence: a Random Forest Approach,
Maddalena Cavicchioli, Angeliki Papana, Ariadni Papana Dagiasis and Barbara Pistoresi, from University of Modena and Reggio E., Dept. of Economics "Marco Biagi" (2016)
Keywords: Central bank independence, political and economic determinants, Random survival forests

Estimating Discrete Choice Models with Random Forests,
Ningyuan Chen, Guillermo Gallego and Zhuodong Tang, from Springer (2021)
Keywords: Discrete choice model, Random forest, Machine learning, Online retailing

Targeting predictors in random forest regression,
Daniel Borup, Bent Jesper Christensen, Nicolaj Søndergaard Mühlbach and Mikkel Slot Nielsen, in International Journal of Forecasting (2023)
Keywords: Random forests; Targeted predictors; High-dimensional forecasting; Weak predictors; Variable selection;

Two Applications of Random Spanning Forests,
L. Avena and A. Gaudillière, in Journal of Theoretical Probability (2018)
Keywords: Finite networks, Spectral analysis, Spanning forests, Determinantal processes, Random sets, Hitting times, Coalescence and fragmentation, Local equilibria

Debiasing SHAP scores in random forests,
Markus Loecher, in AStA Advances in Statistical Analysis (2024)
Keywords: Interpretable machine learning, Feature importance, Random forests, SHAP values, Explainable artificial intelligence

Soil Erosion Status Prediction Using a Novel Random Forest Model Optimized by Random Search Method,
Zahraa Tarek, Ahmed M. Elshewey, Samaa M. Shohieb, Abdelghafar M. Elhady, Noha E. El-Attar, Sherif Elseuofi and Mahmoud Y. Shams, in Sustainability (2023)
Keywords: soil erosion; random forest; random search; classification; evaluation metrics

MCS-RF: mobile crowdsensing–based air quality estimation with random forest,
Cheng Feng, Ye Tian, Xiangyang Gong, Xirong Que and Wendong Wang, in International Journal of Distributed Sensor Networks (2018)
Keywords: Air quality estimation; mobile crowdsensing; semi-supervised random forest; online random forest; data fusion

Ensemble of optimal trees, random forest and random projection ensemble classification,
Zardad Khan, Asma Gul, Aris Perperoglou, Miftahuddin Miftahuddin, Osama Mahmoud, Werner Adler and Berthold Lausen, in Advances in Data Analysis and Classification (2020)
Keywords: Ensemble classification, Ensemble regression, Random forest, Random projection ensemble classification, Accuracy and diversity

The Influence of South East Asia Forest Fires on Ambient Particulate Matter Concentrations in Singapore: An Ecological Study Using Random Forest and Vector Autoregressive Models,
Jayanthi Rajarethinam, Joel Aik and Jing Tian, in IJERPH (2020)
Keywords: air quality; forest fires; random forest model; vector autoregressive model

Analyzing walking route choice through built environments using random forests and discrete choice techniques,
Calvin P Tribby, Harvey J Miller, Barbara B Brown, Carol M Werner and Ken R Smith, in Environment and Planning B (2017)
Keywords: Walkability; route choice; random forests; built environment

Check On-Time Performance of Domestic Airlines Using Random Forest Machine Learning Analysis,
Ariyono Setiawan, Efendi Efendi, Ahmad Mubarok, Kukuh Tri Prasetyo and Untung Lestari Nur Wibowo, in Technium Social Sciences Journal (2023)
Keywords: On Time Performance, Machine Learning, Random Forest

Spatio-temporal estimation of the daily cases of COVID-19 in worldwide using random forest machine learning algorithm,
Cafer Mert Yeşilkanat, in Chaos, Solitons & Fractals (2020)
Keywords: COVID-19; Random forest; Machine learning; Estimating; Mapping;

COVID-19 Mortality Prediction Using Machine Learning-Integrated Random Forest Algorithm under Varying Patient Frailty,
Erwin Cornelius, Olcay Akman and Dan Hrozencik, in Mathematics (2021)
Keywords: machine learning; random forest; neural network

Evaluation of Land Suitability for Olive ( Olea europaea L.) Cultivation Using the Random Forest Algorithm,
Ayse Yavuz Ozalp and Halil Akinci, in Agriculture (2023)
Keywords: land suitability; olive cultivation; random forest; Artvin

Generating a spatial coverage plan for the emergency medical service on a regional scale: Empirical versus random forest modelling approach,
Martin Dolejš, Jan Purchard and Adam Javorčák, in Journal of Transport Geography (2020)
Keywords: EMS; Ambulance; Travel time; Random forest; GPS;

A fair grid connection cost-sharing model for electricity based on the random forest machine learning method,
Li Xie and Chun Kong, in Utilities Policy (2024)
Keywords: Dedicated grid; Connection cost-sharing; Random forest;

Analysis of Geological Hazard Susceptibility of Landslides in Muli County Based on Random Forest Algorithm,
Xiaoyi Wu, Yuanbao Song, Wei Chen, Guichuan Kang, Rui Qu, Zhifei Wang, Jiaxian Wang, Pengyi Lv and Han Chen, in Sustainability (2023)
Keywords: random forest; landslide; susceptibility analysis; Muli County

Effectiveness of Random Forest Model in Predicting Stock Prices of Solar Energy Companies in India,
Bharat Kumar Meher, Abhishek Anand, Sunil Kumar, Ramona Birau and Manohar Sing, in International Journal of Energy Economics and Policy (2024)
Keywords: Energy, Machine Learning, Random Forest, Forecasting

Modelling Coal Dust Explosibility of Khyber Pakhtunkhwa Coal Using Random Forest Algorithm,
Amad Ullah Khan, Saad Salman, Khan Muhammad and Mudassar Habib, in Energies (2022)
Keywords: coal dust explosibility; random forest; SHAP

Identification of representative trees in random forests based on a new tree-based distance measure,
Björn-Hergen Laabs, Ana Westenberger and Inke R. König, in Advances in Data Analysis and Classification (2024)
Keywords: Random forest, Representative trees, Tree distance, Interpretability

Geological Disaster Susceptibility Evaluation Using a Random Forest Empowerment Information Quantity Model,
Rongwei Li, Shucheng Tan, Mingfei Zhang, Shaohan Zhang, Haishan Wang and Lei Zhu, in Sustainability (2024)
Keywords: geological hazards; susceptibility; random forests; informativeness

QCM: Stata module to implement quantile control method (QCM) via Random Forest,
Guanpeng Yan and Qiang Chen, from Boston College Department of Economics (2024)
Keywords: quantile estimates, random forest, treatment effects

SRTREE: Stata module to implement regression trees via optimal pruning, bagging, random forests, and boosting methods,
Giovanni Cerulli, from Boston College Department of Economics (2022)
Keywords: regression trees, pruning, bagging, random forests, boosting

SCTREE: Stata module to implement classification trees via optimal pruning, bagging, random forests, and boosting methods,
Giovanni Cerulli, from Boston College Department of Economics (2022)
Keywords: classification trees, pruning, bagging, random forests, boosting

Pronóstico de Infl ación de Corto Plazo en Argentina con Modelos Random Forest,
Federico Forte, from Red Nacional de Investigadores en Economía (RedNIE) (2024)
Keywords: Inflación, Random Forest, Pronóstico, Machine Learning, Econometría

Evaluation of Liquefaction-Induced Settlement Using Random Forest and REP Tree Models: Taking Pohang Earthquake as a Case of Illustration,
Mahmood Ahmad, Xiaowei Tang and Feezan Ahmad, from IntechOpen
Keywords: liquefaction, random forest, REP tree, settlement

Soil Mapping Based on the Integration of the Similarity-Based Approach and Random Forests,
Desheng Wang and A-Xing Zhu, in Land (2020)
Keywords: digital soil mapping; similarity-based approach; random forests; method integration

Random-forest-based failure prediction for hard disk drives,
Jing Shen, Jian Wan, Se-Jung Lim and Lifeng Yu, in International Journal of Distributed Sensor Networks (2018)
Keywords: Failure prediction; random forest; clustering algorithm; hard disk drives

A comparison of random forest and logistic regression model in credit scoring of rural households,
Hong Nhung Do and Michel Simioni, from HAL (2021)
Keywords: Random forest,Logistic regression,VARHS,Credit assessment,Machine learning

Credit Spread Approximation and Improvement using Random Forest Regression,
Mathieu Mercadier and Jean-Pierre Lardy, from HAL (2019)
Keywords: Risk Analysis,Finance,Structural Model,Random Forests,Credit Default Swaps

Credit spread approximation and improvement using random forest regression,
Mathieu Mercadier and Jean-Pierre Lardy, from HAL (2019)
Keywords: Risk Analysis,Credit Default Swaps,Random Forests,Finance,Structural Model

Predicting Countries’ Development Levels Using the Decision Tree and Random Forest Methods,
Batuhan Özkan, Coşkun Parim and Erhan Çene, in EKOIST Journal of Econometrics and Statistics (2023)
Keywords: Development Level, Decision Tree, Random Forest, Fertility Rate, Machine Learning

Green production cycle mining of mass production based on random forest algorithm,
Tao Xiao, Tao Zhang and Ning Zhang, in International Journal of Product Development (2020)
Keywords: random forest algorithm; product; green production cycle; mining.

Classification of wheat seeds using image processing and fuzzy clustered random forest,
Parminder Singh, Anand Nayyar, Simranjeet Singh and Avinash Kaur, in International Journal of Agricultural Resources, Governance and Ecology (2020)
Keywords: classification; wheat seeds; image processing; fuzzy clustering; random forest; agriculture.

A Traffic Event Detection Method Based on Random Forest and Permutation Importance,
Ziyi Su, Qingchao Liu, Chunxia Zhao and Fengming Sun, in Mathematics (2022)
Keywords: traffic event detection; variable selection method; improved random forest

Random Forest Regression in Predicting Students’ Achievements and Fuzzy Grades,
Daniel Doz, Mara Cotič and Darjo Felda, in Mathematics (2023)
Keywords: national assessments; fuzzy logic; random forest regression; prediction

Do industry returns predict the stock market? A reprise using the random forest,
Cetin Ciner, in The Quarterly Review of Economics and Finance (2019)
Keywords: Market risk premium; Forecasting; Industry returns; Random forest;

Credit spread approximation and improvement using random forest regression,
Mathieu Mercadier and Jean-Pierre Lardy, in European Journal of Operational Research (2019)
Keywords: Risk analysis; Finance; Structural model; Random forests; Credit default swaps;

Consistent estimation of residual variance with random forest Out-Of-Bag errors,
Burim Ramosaj and Markus Pauly, in Statistics & Probability Letters (2019)
Keywords: Residual variance; Consistency; Out-Of-Bag samples; Random forest; Statistical learning;

Forecasting Bitcoin with technical analysis: A not-so-random forest?,
Nikola Gradojevic, Dragan Kukolj, Robert Adcock and Vladimir Djakovic, in International Journal of Forecasting (2023)
Keywords: Bitcoin; Deep learning; Random forest; Forecasting; Technical analysis; Market sentiment;

A Random Forests Approach to Predicting Clean Energy Stock Prices,
Perry Sadorsky, in JRFM (2021)
Keywords: clean energy stock prices; forecasting; machine learning; random forests

On the Oracle Properties of Bayesian Random Forest for Sparse High-Dimensional Gaussian Regression,
Oyebayo Ridwan Olaniran and Ali Rashash R. Alzahrani, in Mathematics (2023)
Keywords: random forest; oracle property; variable selection; Bayesian analysis; asymptotic normality

The Importance of Economic Variables on London Real Estate Market: A Random Forest Approach,
Susanna Levantesi and Gabriella Piscopo, in Risks (2020)
Keywords: house price prediction; real estate; machine learning; random forest

The Determinants of Mathematics Achievement: A Gender Perspective Using Multilevel Random Forest,
Alice Bertoletti, Marta Cannistrà, Melisa Diaz Lema, Chiara Masci, Anna Mergoni, Lidia Rossi and Mara Soncin, in Economies (2023)
Keywords: mathematics achievement; comparative analysis; gender gap; random forest

A risk identification method for abnormal accounting data based on weighted random forest,
Yan Shi, in International Journal of Information Technology and Management (2024)
Keywords: SMOTE algorithm; weighted random forest; loss function; negative gradient fitting.

Pricing Bermudan options using regression trees/random forests,
Zineb El Filali Ech-Chafiq, Pierre Henry Labordère and Jérôme Lelong, from HAL (2023)
Keywords: Regression trees,Random forests,Bermudan options,Optimal stopping

Two-Stage Least Squares Random Forests with a Replication of Angrist and Evans (1998),
Philipp Kugler and Martin Biewen, from Verein für Socialpolitik / German Economic Association (2020)
Keywords: machine learning, generalized random forests, fertility, instrumental variable estimation

Two-stage least squares random forests with an application to Angrist and Evans (1998),
Martin Biewen and Philipp Kugler, in Economics Letters (2021)
Keywords: Machine learning; Generalized random forests; Fertility; Instrumental variable estimation;

Wound Tissue Segmentation and Classification Using U-Net and Random Forest,
V. S. Arjun, Leena Chandrasekhar and K. U. Jaseena, in Journal of Information & Knowledge Management (JIKM) (2024)
Keywords: Wound tissue, segmentation, U-Net, classification, Random Forest, k-means

Predictive Power of Random Forests in Analyzing Risk Management in Islamic Banking,
Ahmet Faruk Aysan, Bekir Sait Ciftler and Ibrahim Musa Unal, in JRFM (2024)
Keywords: risk management; Islamic banks; survey analysis; random forest; machine learning

Forecasting European high-growth Firms - A Random Forest Approach,
Jurij Weinblat, in Journal of Industry, Competition and Trade (2018)
Keywords: High-growth firms, Random forest, Forecasting, Variable importance

Multiple Imputation and Random Forests (MIRF) for Unobservable, High-Dimensional Data,
Nonyane Bareng A. S. and Foulkes Andrea S., in The International Journal of Biostatistics (2007)
Keywords: recursive partitioning, random forests, haplotype, genotype, phase, HIV-1, lipids

Geological Disaster Susceptibility Evaluation of a Random-Forest-Weighted Deterministic Coefficient Model,
Shaohan Zhang, Shucheng Tan, Jinxuan Zhou, Yongqi Sun, Duanyu Ding and Jun Li, in Sustainability (2023)
Keywords: geological hazard; susceptibility; random forests; certainty factor; Huize County

Spatial Distribution Prediction of Soil Heavy Metals Based on Random Forest Model,
Shunqi Nie, Honghua Chen, Xinxin Sun and Yunce An, in Sustainability (2024)
Keywords: soil heavy metals; random forest; spatial interpolation; spatial distribution prediction

A Comparison between Spatial Econometric Models and Random Forest for Modeling Fire Occurrence,
Chao Song, Mei-Po Kwan, Weiguo Song and Jiping Zhu, in Sustainability (2017)
Keywords: fire risk; Random Forest; spatial econometric models; autocorrelation; residuals