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Feature Selection with the Boruta Package

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Cited by:

  1. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
  2. Schrader, Silja & Graham, Sonia & Campbell, Rebecca & Height, Kaitlyn & Hawkes, Gina, 2024. "Grower attitudes and practices toward area-wide management of cropping weeds in Australia," Land Use Policy, Elsevier, vol. 137(C).
  3. Hamed Ahmadpour & Ommolbanin Bazrafshan & Elham Rafiei-Sardooi & Hossein Zamani & Thomas Panagopoulos, 2021. "Gully Erosion Susceptibility Assessment in the Kondoran Watershed Using Machine Learning Algorithms and the Boruta Feature Selection," Sustainability, MDPI, vol. 13(18), pages 1-24, September.
  4. Samuel Asante Gyamerah & Ning Cai, 2021. "Two-Stage Hybrid Machine Learning Model for High-Frequency Intraday Bitcoin Price Prediction Based on Technical Indicators, Variational Mode Decomposition, and Support Vector Regression," Complexity, Hindawi, vol. 2021, pages 1-15, December.
  5. Muhammad Nadim Hanif & Khurrum S. Mughal & Javed Iqbal, 2018. "A Thick ANN Model for Forecasting Inflation," SBP Working Paper Series 99, State Bank of Pakistan, Research Department.
  6. Peiró-Signes, Ángel & Segarra-Oña, Marival & Trull-Domínguez, Óscar & Sánchez-Planelles, Joaquín, 2022. "Exposing the ideal combination of endogenous–exogenous drivers for companies’ ecoinnovative orientation: Results from machine-learning methods," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
  7. Esteban Bravo-López & Tomás Fernández Del Castillo & Chester Sellers & Jorge Delgado-García, 2023. "Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods," Land, MDPI, vol. 12(6), pages 1-28, May.
  8. Maryam A. Y. Al-Nesf & Houari B. Abdesselem & Ilham Bensmail & Shahd Ibrahim & Walaa A. H. Saeed & Sara S. I. Mohammed & Almurtada Razok & Hashim Alhussain & Reham M. A. Aly & Muna Al Maslamani & Khal, 2022. "Prognostic tools and candidate drugs based on plasma proteomics of patients with severe COVID-19 complications," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
  9. Katarzyna Leśniewska-Napierała & Tomasz Napierała & Marta Nalej, 2024. "Geographical Variability of Set-Aside in Poland: Environmental and Anthropogenic Impacts on the Implementation of Complementary EU Instrument," Sustainability, MDPI, vol. 16(24), pages 1-23, December.
  10. Hakan Pabuccu & Adrian Barbu, 2023. "Feature Selection with Annealing for Forecasting Financial Time Series," Papers 2303.02223, arXiv.org, revised Feb 2024.
  11. Galati, Antonino & Coticchio, Alessandro & Peiró-Signes, Ángel, 2023. "Identifying the factors affecting citizens' willingness to participate in urban forest governance: Evidence from the municipality of Palermo, Italy," Forest Policy and Economics, Elsevier, vol. 155(C).
  12. Bram Janssens & Matthias Bogaert & Mathijs Maton, 2023. "Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents," Annals of Operations Research, Springer, vol. 325(1), pages 557-588, June.
  13. Jamei, Mehdi & Maroufpoor, Saman & Aminpour, Younes & Karbasi, Masoud & Malik, Anurag & Karimi, Bakhtiar, 2022. "Developing hybrid data-intelligent method using Boruta-random forest optimizer for simulation of nitrate distribution pattern," Agricultural Water Management, Elsevier, vol. 270(C).
  14. Jin Li & Maggie Tran & Justy Siwabessy, 2016. "Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-29, February.
  15. Abolfazl Mollalo & Kiara M. Rivera & Behzad Vahedi, 2020. "Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States," IJERPH, MDPI, vol. 17(12), pages 1-13, June.
  16. Zulfiqar Ali & Ijaz Hussain & Muhammad Faisal & Dost Muhammad Khan & Rizwan Niaz & Elsayed Elsherbini Elashkar & Alaa Mohamd Shoukry, 2020. "Propagation of the Multi-Scalar Aggregative Standardized Precipitation Temperature Index and its Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 699-714, January.
  17. Alexander C Keyel & Oliver Elison Timm & P Bryon Backenson & Catharine Prussing & Sarah Quinones & Kathleen A McDonough & Mathias Vuille & Jan E Conn & Philip M Armstrong & Theodore G Andreadis & Laur, 2019. "Seasonal temperatures and hydrological conditions improve the prediction of West Nile virus infection rates in Culex mosquitoes and human case counts in New York and Connecticut," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-32, June.
  18. Tong, Jianfeng & Liu, Zhenxing & Zhang, Yong & Zheng, Xiujuan & Jin, Junyang, 2023. "Improved multi-gate mixture-of-experts framework for multi-step prediction of gas load," Energy, Elsevier, vol. 282(C).
  19. Andrea Rigamonti, 2024. "Can machine learning make technical analysis work?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 38(3), pages 399-412, September.
  20. Yingjie Zhu & Jiageng Ma & Fangqing Gu & Jie Wang & Zhijuan Li & Youyao Zhang & Jiani Xu & Yifan Li & Yiwen Wang & Xiangqun Yang, 2023. "Price Prediction of Bitcoin Based on Adaptive Feature Selection and Model Optimization," Mathematics, MDPI, vol. 11(6), pages 1-22, March.
  21. Manuel Sánchez-Montañés & Pablo Rodríguez-Belenguer & Antonio J. Serrano-López & Emilio Soria-Olivas & Yasser Alakhdar-Mohmara, 2020. "Machine Learning for Mortality Analysis in Patients with COVID-19," IJERPH, MDPI, vol. 17(22), pages 1-20, November.
  22. Elias Cavalcante-Filho & Flavio Abdenur, Rodrigo De Losso, 2018. "Machine learning applied to accounting variables yields the risk-return metrics of private company portfolios," Working Papers, Department of Economics 2018_23, University of São Paulo (FEA-USP).
  23. Pang, Junheng & Dong, Sheng, 2023. "A novel multivariable hybrid model to improve short and long-term significant wave height prediction," Applied Energy, Elsevier, vol. 351(C).
  24. Danying Du & Baozhong He & Xuefeng Luo & Shilong Ma & Yaning Song & Wen Yang, 2024. "Spatio-Temporal Variation Analysis of Soil Salinization in the Ougan-Kuqa River Oasis of China," Sustainability, MDPI, vol. 16(7), pages 1-22, March.
  25. Cooray, Upul & Watt, Richard G. & Tsakos, Georgios & Heilmann, Anja & Hariyama, Masanori & Yamamoto, Takafumi & Kuruppuarachchige, Isuruni & Kondo, Katsunori & Osaka, Ken & Aida, Jun, 2021. "Importance of socioeconomic factors in predicting tooth loss among older adults in Japan: Evidence from a machine learning analysis," Social Science & Medicine, Elsevier, vol. 291(C).
  26. Jamei, Mehdi & Ali, Mumtaz & Karbasi, Masoud & Xiang, Yong & Ahmadianfar, Iman & Yaseen, Zaher Mundher, 2022. "Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach," Applied Energy, Elsevier, vol. 326(C).
  27. Asma Shaheen & Javed Iqbal, 2018. "Spatial Distribution and Mobility Assessment of Carcinogenic Heavy Metals in Soil Profiles Using Geostatistics and Random Forest, Boruta Algorithm," Sustainability, MDPI, vol. 10(3), pages 1-20, March.
  28. Nkiruka C. Atuegwu & Cheryl Oncken & Reinhard C. Laubenbacher & Mario F. Perez & Eric M. Mortensen, 2020. "Factors Associated with E-Cigarette Use in U.S. Young Adult Never Smokers of Conventional Cigarettes: A Machine Learning Approach," IJERPH, MDPI, vol. 17(19), pages 1-16, October.
  29. Matthew James Grainger & Lusine Aramyan & Simone Piras & Thomas Edward Quested & Simone Righi & Marco Setti & Matteo Vittuari & Gavin Bruce Stewart, 2018. "Model selection and averaging in the assessment of the drivers of household food waste to reduce the probability of false positives," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-16, February.
  30. Jihong Qu & Kun Ren & Xiaoyu Shi, 2021. "Binary Grey Wolf Optimization-Regularized Extreme Learning Machine Wrapper Coupled with the Boruta Algorithm for Monthly Streamflow Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(3), pages 1029-1045, February.
  31. Simon Besnard & Nuno Carvalhais & M Altaf Arain & Andrew Black & Benjamin Brede & Nina Buchmann & Jiquan Chen & Jan G P W Clevers & Loïc P Dutrieux & Fabian Gans & Martin Herold & Martin Jung & Yoshik, 2019. "Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-22, February.
  32. Seung-Hun Lee & Hyeon-Seong Ju & Sang-Hun Lee & Sung-Woo Kim & Hun-Young Park & Seung-Wan Kang & Young-Eun Song & Kiwon Lim & Hoeryong Jung, 2021. "Estimation of Health-Related Physical Fitness (HRPF) Levels of the General Public Using Artificial Neural Network with the National Fitness Award (NFA) Datasets," IJERPH, MDPI, vol. 18(19), pages 1-13, October.
  33. Gordana Kaplan & Mateo Gašparović & Onur Kaplan & Vancho Adjiski & Resul Comert & Mohammad Asef Mobariz, 2023. "Machine Learning-Based Classification of Asbestos-Containing Roofs Using Airborne RGB and Thermal Imagery," Sustainability, MDPI, vol. 15(7), pages 1-16, March.
  34. Carolina Alves Costa Silva & Gianmarco Piccinno & Déborah Suissa & Mélanie Bourgin & Gerty Schreibelt & Sylvère Durand & Roxanne Birebent & Marine Fidelle & Cissé Sow & Fanny Aprahamian & Paolo Manghi, 2024. "Influence of microbiota-associated metabolic reprogramming on clinical outcome in patients with melanoma from the randomized adjuvant dendritic cell-based MIND-DC trial," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  35. Mariana Yamada & Leonardo Vinicius Thiesen & Fernando Henrique Iost Filho & Pedro Takao Yamamoto, 2024. "Hyperspectral Imaging and Machine Learning: A Promising Tool for the Early Detection of Tetranychus urticae Koch Infestation in Cotton," Agriculture, MDPI, vol. 14(9), pages 1-18, September.
  36. Ramón Ferri-García & María del Mar Rueda, 2022. "Variable selection in Propensity Score Adjustment to mitigate selection bias in online surveys," Statistical Papers, Springer, vol. 63(6), pages 1829-1881, December.
  37. Francesco Sartor & Jonathan P. Moore & Hans-Peter Kubis, 2021. "Plasma Interleukin-10 and Cholesterol Levels May Inform about Interdependences between Fitness and Fatness in Healthy Individuals," IJERPH, MDPI, vol. 18(4), pages 1-19, February.
  38. Tomasz Szul & Sylwester Tabor & Krzysztof Pancerz, 2021. "Application of the BORUTA Algorithm to Input Data Selection for a Model Based on Rough Set Theory (RST) to Prediction Energy Consumption for Building Heating," Energies, MDPI, vol. 14(10), pages 1-13, May.
  39. Ángel Peiró‐Signes & Inés Díez‐Martínez & Marival Segarra‐Oña, 2024. "The drivers of cooperation for innovation and the role of environmental orientation," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 31(4), pages 2929-2952, July.
  40. Sunoj, S. & Polson, Benjamin & Vaish, Isha & Marcaida, Manuel & Longchamps, Louis & van Aardt, Jan & Ketterings, Quirine M., 2024. "Corn grain and silage yield class prediction for zone delineation using high-resolution satellite imagery," Agricultural Systems, Elsevier, vol. 218(C).
  41. Dai, Hongyan & Xiao, Qin & Chen, Songlin & Zhou, Weihua, 2023. "Data-driven demand forecast for O2O operations: An adaptive hierarchical incremental approach," International Journal of Production Economics, Elsevier, vol. 259(C).
  42. Seonhui Noh & Seungyub Lee, 2024. "Forecasting Meteorological Drought Conditions in South Korea Using a Data-Driven Model with Lagged Global Climate Variability," Sustainability, MDPI, vol. 16(15), pages 1-21, July.
  43. Sašo Karakatič, 2020. "EvoPreprocess—Data Preprocessing Framework with Nature-Inspired Optimization Algorithms," Mathematics, MDPI, vol. 8(6), pages 1-29, June.
  44. Jiří Šandera & Přemysl Štych, 2020. "Selecting Relevant Biological Variables Derived from Sentinel-2 Data for Mapping Changes from Grassland to Arable Land Using Random Forest Classifier," Land, MDPI, vol. 9(11), pages 1-20, October.
  45. Maik Pietzner & Eleanor Wheeler & Julia Carrasco-Zanini & Nicola D. Kerrison & Erin Oerton & Mine Koprulu & Jian’an Luan & Aroon D. Hingorani & Steve A. Williams & Nicholas J. Wareham & Claudia Langen, 2021. "Synergistic insights into human health from aptamer- and antibody-based proteomic profiling," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  46. Giorgos Foutzopoulos & Nikolaos Pandis & Michail Tsagris, 2024. "Predicting Full Retirement Attainment of NBA Players," Working Papers 2403, University of Crete, Department of Economics.
  47. Ramaharo, Franck Maminirina & RANDRIAMIFIDY, Michael Fitiavana, 2023. "Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms," AfricArxiv pfrhx, Center for Open Science.
  48. Umme Marzia Haque & Enamul Kabir & Rasheda Khanam, 2021. "Detection of child depression using machine learning methods," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-13, December.
  49. Yvan Devaux & Lu Zhang & Andrew I. Lumley & Kanita Karaduzovic-Hadziabdic & Vincent Mooser & Simon Rousseau & Muhammad Shoaib & Venkata Satagopam & Muhamed Adilovic & Prashant Kumar Srivastava & Costa, 2024. "Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  50. Iain S. Forrest & Ben O. Petrazzini & Áine Duffy & Joshua K. Park & Anya J. O’Neal & Daniel M. Jordan & Ghislain Rocheleau & Girish N. Nadkarni & Judy H. Cho & Ashira D. Blazer & Ron Do, 2023. "A machine learning model identifies patients in need of autoimmune disease testing using electronic health records," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  51. Ghosh, Indranil & Chaudhuri, Tamal Datta & Alfaro-Cortés, Esteban & Gámez, Matías & García, Noelia, 2022. "A hybrid approach to forecasting futures prices with simultaneous consideration of optimality in ensemble feature selection and advanced artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
  52. Kresova, Svetlana & Hess, Sebastian, 2021. "Determinants of Regional Raw Milk Prices in Russia," 2021 Conference, August 17-31, 2021, Virtual 315064, International Association of Agricultural Economists.
  53. Samuel Asante Gyamerah, 2019. "Are Bitcoins price predictable? Evidence from machine learning techniques using technical indicators," Papers 1909.01268, arXiv.org.
  54. Andrea Albergoni & Florentina J. Hettinga & Wim Stut & Francesco Sartor, 2020. "Factors Influencing Walking and Exercise Adherence in Healthy Older Adults Using Monitoring and Interfacing Technology: Preliminary Evidence," IJERPH, MDPI, vol. 17(17), pages 1-18, August.
  55. Alexander Kirpich & Elizabeth A Ainsworth & Jessica M Wedow & Jeremy R B Newman & George Michailidis & Lauren M McIntyre, 2018. "Variable selection in omics data: A practical evaluation of small sample sizes," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-19, June.
  56. Chunyang Huang & Shaoliang Zhang, 2023. "Explainable artificial intelligence model for identifying Market Value in Professional Soccer Players," Papers 2311.04599, arXiv.org, revised Nov 2023.
  57. Reza Arabi Belaghi & Joseph Beyene & Sarah D McDonald, 2021. "Prediction of preterm birth in nulliparous women using logistic regression and machine learning," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-22, June.
  58. Caperna, Giulio & Colagrossi, Marco & Geraci, Andrea & Mazzarella, Gianluca, 2020. "Googling Unemployment During the Pandemic: Inference and Nowcast Using Search Data," JRC Working Papers in Economics and Finance 2020-04, Joint Research Centre, European Commission.
  59. Joseph, Lionel P. & Deo, Ravinesh C. & Prasad, Ramendra & Salcedo-Sanz, Sancho & Raj, Nawin & Soar, Jeffrey, 2023. "Near real-time wind speed forecast model with bidirectional LSTM networks," Renewable Energy, Elsevier, vol. 204(C), pages 39-58.
  60. Conor Waldock & Bernhard Wegscheider & Dario Josi & Bárbara Borges Calegari & Jakob Brodersen & Luiz Jardim de Queiroz & Ole Seehausen, 2024. "Deconstructing the geography of human impacts on species’ natural distribution," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  61. Hakan Pabuccu & Adrian Barbu, 2024. "Feature selection with annealing for forecasting financial time series," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-26, December.
  62. Guillaume Belly & Lukas Boeckelmann & Carlos Mateo Caicedo Graciano & Alberto Di Iorio & Klodiana Istrefi & Vasileios Siakoulis & Arthur Stalla‐Bourdillon, 2023. "Forecasting sovereign risk in the Euro area via machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(3), pages 657-684, April.
  63. Celico, Andrea & Rode, Martin & Rodriguez-Carreño, Ignacio, 2024. "Will the real populists please stand up? A machine learning index of party populism," European Journal of Political Economy, Elsevier, vol. 82(C).
  64. Nawin Raj, 2022. "Prediction of Sea Level with Vertical Land Movement Correction Using Deep Learning," Mathematics, MDPI, vol. 10(23), pages 1-23, November.
  65. Svetlana Kresova & Sebastian Hess, 2022. "Identifying the Determinants of Regional Raw Milk Prices in Russia Using Machine Learning," Agriculture, MDPI, vol. 12(7), pages 1-18, July.
  66. Sara Saadatmand & Khodakaram Salimifard & Reza Mohammadi & Alex Kuiper & Maryam Marzban & Akram Farhadi, 2023. "Using machine learning in prediction of ICU admission, mortality, and length of stay in the early stage of admission of COVID-19 patients," Annals of Operations Research, Springer, vol. 328(1), pages 1043-1071, September.
  67. Tao, Jiawei & Dai, Hongyan & Chen, Weiwei & Jiang, Hai, 2023. "The value of personalized dispatch in O2O on-demand delivery services," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1022-1035.
  68. Tang, Rui & Yildiz, Baran & Leong, Philip H.W. & Vassallo, Anthony & Dore, Jonathon, 2019. "Residential battery sizing model using net meter energy data clustering," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  69. Marc Deffland & Claudia Spies & Bjoern Weiss & Niklas Keller & Mirjam Jenny & Jochen Kruppa & Felix Balzer, 2020. "Effects of pain, sedation and delirium monitoring on clinical and economic outcome: A retrospective study," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-14, September.
  70. Raihan Rafif & Sandiaga Swahyu Kusuma & Siti Saringatin & Giara Iman Nanda & Pramaditya Wicaksono & Sanjiwana Arjasakusuma, 2021. "Crop Intensity Mapping Using Dynamic Time Warping and Machine Learning from Multi-Temporal PlanetScope Data," Land, MDPI, vol. 10(12), pages 1-18, December.
  71. Peter L. Watson & Marika Koukoula & Emmanouil Anagnostou, 2021. "Influence of the Characteristics of Weather Information in a Thunderstorm-Related Power Outage Prediction System," Forecasting, MDPI, vol. 3(3), pages 1-20, August.
  72. Yiping Peng & Ting Wang & Shujuan Xie & Zhenhua Liu & Chenjie Lin & Yueming Hu & Jianfang Wang & Xiaoyun Mao, 2023. "Estimation of Soil Cations Based on Visible and Near-Infrared Spectroscopy and Machine Learning," Agriculture, MDPI, vol. 13(6), pages 1-12, June.
  73. Park, Eunhye & Park, Jinah & Hu, Mingming, 2021. "Tourism demand forecasting with online news data mining," Annals of Tourism Research, Elsevier, vol. 90(C).
  74. Wei Fang & Ying Liu & Chun Xu & Xingguang Luo & Kesheng Wang, 2024. "Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022," IJERPH, MDPI, vol. 21(11), pages 1-14, November.
  75. Wei Pan & Jonathan Flint & Liat Shenhav & Tianli Liu & Mingming Liu & Bin Hu & Tingshao Zhu, 2019. "Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-14, June.
  76. Bhaskar Tripathi & Rakesh Kumar Sharma, 2023. "Modeling Bitcoin Prices using Signal Processing Methods, Bayesian Optimization, and Deep Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1919-1945, December.
  77. Matara Caroline Mongina & Nyambane Simpson Osano & Yusuf Amir Okeyo & Ochungo Elisha Akech & Khattak Afaq, 2024. "Classification of Particulate Matter (PM2.5) Concentrations Using Feature Selection and Machine Learning Strategies," LOGI – Scientific Journal on Transport and Logistics, Sciendo, vol. 15(1), pages 85-96.
  78. Manuel S. González Canché, 2022. "Post-purchase Federal Financial Aid: How (in)Effective is the IRS’s Student Loan Interest Deduction (SLID) in Reaching Lower-Income Taxpayers and Students?," Research in Higher Education, Springer;Association for Institutional Research, vol. 63(6), pages 933-986, September.
  79. David Stephens & Markus Diesing, 2014. "A Comparison of Supervised Classification Methods for the Prediction of Substrate Type Using Multibeam Acoustic and Legacy Grain-Size Data," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-14, April.
  80. Dawid Maciejewski & Krzysztof Mudryk & Maciej Sporysz, 2024. "Forecasting Electricity Production in a Small Hydropower Plant (SHP) Using Artificial Intelligence (AI)," Energies, MDPI, vol. 17(24), pages 1-23, December.
  81. F. Michele & E. Stagnini & D. Pera & B. Rubino & R. Aloisio & A. Askan & P. Marcati, 2023. "Comparison of machine learning tools for damage classification: the case of L’Aquila 2009 earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(3), pages 3521-3546, April.
  82. Liu, Yu & Qin, Xu & Cai, Zhibo, 2025. "A tree approach for variable selection and its random forest," Computational Statistics & Data Analysis, Elsevier, vol. 202(C).
  83. Gang Chen & Xianju Li & Weitao Chen & Xinwen Cheng & Yujin Zhang & Shengwei Liu, 2014. "Extraction and application analysis of landslide influential factors based on LiDAR DEM: a case study in the Three Gorges area, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 509-526, November.
  84. Baozhong He & Jianli Ding & Wenjiang Huang & Xu Ma, 2023. "Spatiotemporal Variation and Future Predictions of Soil Salinization in the Werigan–Kuqa River Delta Oasis of China," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
  85. Kian Tehranian, 2023. "Can Machine Learning Catch Economic Recessions Using Economic and Market Sentiments?," Papers 2308.16200, arXiv.org.
  86. Ewa Wilk & Małgorzata Krówczyńska & Bogdan Zagajewski, 2019. "Modelling the Spatial Distribution of Asbestos—Cement Products in Poland with the Use of the Random Forest Algorithm," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
  87. Alex Gramegna & Paolo Giudici, 2022. "Shapley Feature Selection," FinTech, MDPI, vol. 1(1), pages 1-9, February.
  88. Carlos Família & Sarah R Dennison & Alexandre Quintas & David A Phoenix, 2015. "Prediction of Peptide and Protein Propensity for Amyloid Formation," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-16, August.
  89. Aivett Bilbao & Nathalie Munoz & Joonhoon Kim & Daniel J. Orton & Yuqian Gao & Kunal Poorey & Kyle R. Pomraning & Karl Weitz & Meagan Burnet & Carrie D. Nicora & Rosemarie Wilton & Shuang Deng & Ziyu , 2023. "PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements," Nature Communications, Nature, vol. 14(1), pages 1-18, December.
  90. Yannick Rothacher & Carolin Strobl, 2024. "Identifying Informative Predictor Variables With Random Forests," Journal of Educational and Behavioral Statistics, , vol. 49(4), pages 595-629, August.
  91. Jaiswal, Rachana & Gupta, Shashank & Tiwari, Aviral Kumar, 2024. "Big data and machine learning-based decision support system to reshape the vaticination of insurance claims," Technological Forecasting and Social Change, Elsevier, vol. 209(C).
  92. Ghosh, Indranil & Datta Chaudhuri, Tamal & Alfaro-Cortés, Esteban & Gámez Martínez, Matías & García Rubio, Noelia, 2021. "Estimating the relative effects of raw material prices, sectoral outlook and market sentiment on stock prices," Resources Policy, Elsevier, vol. 73(C).
  93. Samuel José Silva Soares da Rocha & Flora Magdaline Benitez Romero & Carlos Moreira Miquelino Eleto Torres & Laércio Antônio Gonçalves Jacovine & Sabina Cerruto Ribeiro & Paulo Henrique Villanova & Br, 2023. "Machine Learning: Volume and Biomass Estimates of Commercial Trees in the Amazon Forest," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
  94. Manuel J. García Rodríguez & Vicente Rodríguez Montequín & Francisco Ortega Fernández & Joaquín M. Villanueva Balsera, 2019. "Public Procurement Announcements in Spain: Regulations, Data Analysis, and Award Price Estimator Using Machine Learning," Complexity, Hindawi, vol. 2019, pages 1-20, November.
  95. Faisal Alsayegh & Moh A Alkhamis & Fatima Ali & Sreeja Attur & Nicholas M Fountain-Jones & Mohammad Zubaid, 2022. "Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-15, January.
  96. Dong-Hee Cho & Seung-Hyun Moon & Yong-Hyuk Kim, 2021. "Genetic Feature Selection Applied to KOSPI and Cryptocurrency Price Prediction," Mathematics, MDPI, vol. 9(20), pages 1-19, October.
  97. Jaewon Park & Minsoo Shin, 2022. "An Approach for Variable Selection and Prediction Model for Estimating the Risk-Based Capital (RBC) Based on Machine Learning Algorithms," Risks, MDPI, vol. 10(1), pages 1-20, January.
  98. Sangjin Kim & Jong-Min Kim, 2019. "Two-Stage Classification with SIS Using a New Filter Ranking Method in High Throughput Data," Mathematics, MDPI, vol. 7(6), pages 1-16, May.
  99. Patrick Kenekayoro, 2018. "Identifying named entities in academic biographies with supervised learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 751-765, August.
  100. Chrats Melkonian & Francisco Zorrilla & Inge Kjærbølling & Sonja Blasche & Daniel Machado & Mette Junge & Kim Ib Sørensen & Lene Tranberg Andersen & Kiran R. Patil & Ahmad A. Zeidan, 2023. "Microbial interactions shape cheese flavour formation," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
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