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Building Predictive Models in R Using the caret Package

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Cited by:

  1. Anurag Satpathi & Parul Setiya & Bappa Das & Ajeet Singh Nain & Prakash Kumar Jha & Surendra Singh & Shikha Singh, 2023. "Comparative Analysis of Statistical and Machine Learning Techniques for Rice Yield Forecasting for Chhattisgarh, India," Sustainability, MDPI, vol. 15(3), pages 1-18, February.
  2. Adam P. Dixon & Matthew E. Baker & Erle C. Ellis, 2020. "Agricultural Landscape Composition Linked with Acoustic Measures of Avian Diversity," Land, MDPI, vol. 9(5), pages 1-18, May.
  3. László Pásztor & Katalin Takács & János Mészáros & Gábor Szatmári & Mátyás Árvai & Tibor Tóth & Gyöngyi Barna & Sándor Koós & Zsófia Adrienn Kovács & Péter László & Kitti Balog, 2023. "Indirect Prediction of Salt Affected Soil Indicator Properties through Habitat Types of a Natural Saline Grassland Using Unmanned Aerial Vehicle Imagery," Land, MDPI, vol. 12(8), pages 1-23, July.
  4. Shearman, Timothy M. & Varner, J. Morgan & Hood, Sharon M. & Cansler, C. Alina & Hiers, J. Kevin, 2019. "Modelling post-fire tree mortality: Can random forest improve discrimination of imbalanced data?," Ecological Modelling, Elsevier, vol. 414(C).
  5. Johann Baumgartner & Katharina Gruber & Sofia G. Simoes & Yves-Marie Saint-Drenan & Johannes Schmidt, 2020. "Less Information, Similar Performance: Comparing Machine Learning-Based Time Series of Wind Power Generation to Renewables.ninja," Energies, MDPI, vol. 13(9), pages 1-23, May.
  6. Arthur Novaes de Amorim & Rob Deardon & Vineet Saini, 2021. "A stacked ensemble method for forecasting influenza-like illness visit volumes at emergency departments," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-15, March.
  7. Abhinav Vepa & Amer Saleem & Kambiz Rakhshan & Alireza Daneshkhah & Tabassom Sedighi & Shamarina Shohaimi & Amr Omar & Nader Salari & Omid Chatrabgoun & Diana Dharmaraj & Junaid Sami & Shital Parekh &, 2021. "Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for COVID-19 Inpatients," IJERPH, MDPI, vol. 18(12), pages 1-22, June.
  8. Miguel Godinho de Matos & Pedro Ferreira & Michael D. Smith, 2018. "The Effect of Subscription Video-on-Demand on Piracy: Evidence from a Household-Level Randomized Experiment," Management Science, INFORMS, vol. 64(12), pages 5610-5630, December.
  9. Mirza Čengić & Zoran J. N. Steinmann & Pierre Defourny & Jonathan C. Doelman & Céline Lamarche & Elke Stehfest & Aafke M. Schipper & Mark A. J. Huijbregts, 2023. "Global Maps of Agricultural Expansion Potential at a 300 m Resolution," Land, MDPI, vol. 12(3), pages 1-13, February.
  10. Xiao Xu & Meera Ramanujam & Sudha Visvanathan & Shervin Assassi & Zheng Liu & Li Li, 2020. "Transcriptional insights into pathogenesis of cutaneous systemic sclerosis using pathway driven meta-analysis assisted by machine learning methods," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-20, November.
  11. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
  12. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  13. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
  14. Piaopiao Chen & Agnès H. Michel & Jianzhi Zhang, 2022. "Transposon insertional mutagenesis of diverse yeast strains suggests coordinated gene essentiality polymorphisms," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  15. Zakia Salod & Ozayr Mahomed, 2023. "VPAgs-Dataset4ML: A Dataset to Predict Viral Protective Antigens for Machine Learning-Based Reverse Vaccinology," Data, MDPI, vol. 8(2), pages 1-12, February.
  16. Paulo Infante & Gonçalo Jacinto & Anabela Afonso & Leonor Rego & Pedro Nogueira & Marcelo Silva & Vitor Nogueira & José Saias & Paulo Quaresma & Daniel Santos & Patrícia Góis & Paulo Rebelo Manuel, 2023. "Factors That Influence the Type of Road Traffic Accidents: A Case Study in a District of Portugal," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
  17. Yane Freitas Silva & Rafael Vasconcelos Valadares & Henrique Boriolo Dias & Santiago Vianna Cuadra & Eleanor E. Campbell & Rubens A. C. Lamparelli & Edemar Moro & Rafael Battisti & Marcelo R. Alves & , 2022. "Intense Pasture Management in Brazil in an Integrated Crop-Livestock System Simulated by the DayCent Model," Sustainability, MDPI, vol. 14(6), pages 1-24, March.
  18. Xavier Santamaria & Beatriz Roson & Raul Perez-Moraga & Nandakumar Venkatesan & Maria Pardo-Figuerez & Javier Gonzalez-Fernandez & Jaime Llera-Oyola & Estefania Fernández & Inmaculada Moreno & Andres , 2023. "Decoding the endometrial niche of Asherman’s Syndrome at single-cell resolution," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
  19. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
  20. Khan, Muhammad Asif & Segovia, Juan E.Trinidad & Bhatti, M.Ishaq & Kabir, Asif, 2023. "Corporate vulnerability in the US and China during COVID-19: A machine learning approach," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
  21. Amit Kumar Srivastava & Suranjana Bhaswati Borah & Payel Ghosh Dastidar & Archita Sharma & Debabrat Gogoi & Priyanuz Goswami & Giti Deka & Suryakanta Khandai & Rupam Borgohain & Sudhanshu Singh & Asho, 2023. "Rice-Fallow Targeting for Cropping Intensification through Geospatial Technologies in the Rice Belt of Northeast India," Agriculture, MDPI, vol. 13(8), pages 1-18, July.
  22. Droste, N. & Ring, I. & Santos, R. & Kettunen, M., 2018. "Ecological Fiscal Transfers in Europe – Evidence-Based Design Options for a Transnational Scheme," Ecological Economics, Elsevier, vol. 147(C), pages 373-382.
  23. Brédy, Jhemson & Gallichand, Jacques & Celicourt, Paul & Gumiere, Silvio José, 2020. "Water table depth forecasting in cranberry fields using two decision-tree-modeling approaches," Agricultural Water Management, Elsevier, vol. 233(C).
  24. Banks, Jonathan & Rabbani, Arif & Nadkarni, Kabir & Renaud, Evan, 2020. "Estimating parasitic loads related to brine production from a hot sedimentary aquifer geothermal project: A case study from the Clarke Lake gas field, British Columbia," Renewable Energy, Elsevier, vol. 153(C), pages 539-552.
  25. Sek Won Kong & Christin D Collins & Yuko Shimizu-Motohashi & Ingrid A Holm & Malcolm G Campbell & In-Hee Lee & Stephanie J Brewster & Ellen Hanson & Heather K Harris & Kathryn R Lowe & Adrianna Saada , 2012. "Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-13, December.
  26. Matheus Henrique Dal Molin Ribeiro & Stéfano Frizzo Stefenon & José Donizetti de Lima & Ademir Nied & Viviana Cocco Mariani & Leandro dos Santos Coelho, 2020. "Electricity Price Forecasting Based on Self-Adaptive Decomposition and Heterogeneous Ensemble Learning," Energies, MDPI, vol. 13(19), pages 1-22, October.
  27. Daoud, Adel & Kim, Rockli & Subramanian, S.V., 2019. "Predicting women's height from their socioeconomic status: A machine learning approach," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
  28. Somodi, Imelda & Bede-Fazekas, Ákos & Botta-Dukát, Zoltán & Molnár, Zsolt, 2024. "Confidence and consistency in discrimination: A new family of evaluation metrics for potential distribution models," Ecological Modelling, Elsevier, vol. 491(C).
  29. Christopher Kohl & Marlene Knigge & Galina Baader & Markus Böhm & Helmut Krcmar, 2018. "Anticipating acceptance of emerging technologies using twitter: the case of self-driving cars," Journal of Business Economics, Springer, vol. 88(5), pages 617-642, July.
  30. Ribeiro, Matheus Henrique Dal Molin & da Silva, Ramon Gomes & Ribeiro, Gabriel Trierweiler & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2023. "Cooperative ensemble learning model improves electric short-term load forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
  31. Razavi, Rouzbeh & Gharipour, Amin & Fleury, Martin & Akpan, Ikpe Justice, 2019. "A practical feature-engineering framework for electricity theft detection in smart grids," Applied Energy, Elsevier, vol. 238(C), pages 481-494.
  32. Gero Szepannek, 2022. "An Overview on the Landscape of R Packages for Open Source Scorecard Modelling," Risks, MDPI, vol. 10(3), pages 1-33, March.
  33. David Anaya & Lluís Bermúdez & Jaume Belles-Sampera, 2024. "Modeling paid-ups in life insurance products for risk management," Risk Management, Palgrave Macmillan, vol. 26(3), pages 1-21, September.
  34. Maria Victoria Bascon & Tomohiro Nakata & Satoshi Shibata & Itsuki Takata & Nanami Kobayashi & Yusuke Kato & Shun Inoue & Kazuyuki Doi & Jun Murase & Shunsaku Nishiuchi, 2022. "Estimating Yield-Related Traits Using UAV-Derived Multispectral Images to Improve Rice Grain Yield Prediction," Agriculture, MDPI, vol. 12(8), pages 1-28, August.
  35. Dario Krpan & Jonathan E. Booth & Andreea Damien, 2023. "The positive–negative–competence (PNC) model of psychological responses to representations of robots," Nature Human Behaviour, Nature, vol. 7(11), pages 1933-1954, November.
  36. Oluwaseyi Olalekan Arowosegbe & Martin Röösli & Nino Künzli & Apolline Saucy & Temitope Christina Adebayo-Ojo & Mohamed F. Jeebhay & Mohammed Aqiel Dalvie & Kees de Hoogh, 2021. "Comparing Methods to Impute Missing Daily Ground-Level PM 10 Concentrations between 2010–2017 in South Africa," IJERPH, MDPI, vol. 18(7), pages 1-13, March.
  37. Guopeng Jiang & Miles Grafton & Diane Pearson & Mike Bretherton & Allister Holmes, 2019. "Integration of Precision Farming Data and Spatial Statistical Modelling to Interpret Field-Scale Maize Productivity," Agriculture, MDPI, vol. 9(11), pages 1-22, November.
  38. Nyamekye, Clement & Kwofie, Samuel & Ghansah, Benjamin & Agyapong, Emmanuel & Boamah, Linda Appiah, 2020. "Assessing urban growth in Ghana using machine learning and intensity analysis: A case study of the New Juaben Municipality," Land Use Policy, Elsevier, vol. 99(C).
  39. Franck Ramaharo & Fitiavana Randriamifidy, 2023. "Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms," Papers 2401.13671, arXiv.org.
  40. Caroline K. Glidden & Alyson L. Singleton & Andrew Chamberlin & Roseli Tuan & Raquel G. S. Palasio & Roberta Lima Caldeira & Antônio Miguel V. Monteiro & Kamazima M. M. Lwiza & Ping Liu & Vivian Silva, 2024. "Climate and urbanization drive changes in the habitat suitability of Schistosoma mansoni competent snails in Brazil," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  41. José R. Berrendero & Javier Cárcamo, 2019. "Linear components of quadratic classifiers," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(2), pages 347-377, June.
  42. Jorge Torres & María Muñoz & María Del Carmen Porcel & Sofía Contreras & Francisca Sonia Molina & Guillermo Rus & Olga Ocón-Hernández & Juan Melchor, 2022. "Preliminary Results on the Preinduction Cervix Status by Shear Wave Elastography," Mathematics, MDPI, vol. 10(17), pages 1-14, September.
  43. Yang, Yi & Li, Bingbing & Shi, Peijun & Li, Zhi, 2023. "Assessing spatiotemporally varied ecohydrological effects of apple orchards based on regional-scale estimation of tree distribution and ages," Agricultural Water Management, Elsevier, vol. 287(C).
  44. 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.
  45. Edouard Ribes, 2022. "Using classification techniques to accelerate client discovery: a case study for wealth management services," Working Papers hal-03887759, HAL.
  46. Wen-Long Sun & Sha Hua & Xin-Yu Li & Liang Shen & Hao Wu & Hong-Fang Ji, 2023. "Microbially produced vitamin B12 contributes to the lipid-lowering effect of silymarin," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  47. Yang Yue & Yingjie Jiang & Fan Zhou & Yuantao Jiang & Yiting Long & Kaiyu Wang, 2022. "Reward Uncertainty and Expected Value Enhance Generalization of Episodic Memory," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
  48. Mario Aurelio Martínez-Jiménez & Jose Luis Ramirez-GarciaLuna & Eleazar Samuel Kolosovas-Machuca & Justin Drager & Francisco Javier González, 2018. "Development and validation of an algorithm to predict the treatment modality of burn wounds using thermographic scans: Prospective cohort study," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-16, November.
  49. Yrjö Lappalainen & Matti Lassila & Tanja Heikkilä & Jani Nieminen & Tapani Lehtilä, 2023. "Migrating 120,000 Legacy Publications from Several Systems into a Current Research Information System Using Advanced Data Wrangling Techniques," Publications, MDPI, vol. 11(4), pages 1-16, November.
  50. Li, Xunhuan & Wang, Yongsheng & Wang, Zhaosheng, 2024. "Quantifying the industrial development modes and their capability of realizing the ecological value in rural China," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
  51. Denis S. Zavorotnyuk & Anatoly A. Sorokin & Stanislav I. Pekov & Denis S. Bormotov & Vasiliy A. Eliferov & Konstantin V. Bocharov & Eugene N. Nikolaev & Igor A. Popov, 2023. "Shapley Value as a Quality Control for Mass Spectra of Human Glioblastoma Tissues," Data, MDPI, vol. 8(1), pages 1-9, January.
  52. Alexander Wettstein & Gabriel Jenni & Ida Schneider & Fabienne Kühne & Martin grosse Holtforth & Roberto La Marca, 2023. "Predictors of Psychological Strain and Allostatic Load in Teachers: Examining the Long-Term Effects of Biopsychosocial Risk and Protective Factors Using a LASSO Regression Approach," IJERPH, MDPI, vol. 20(10), pages 1-20, May.
  53. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
  54. M. Ponziani & D. Ponziani & A. Giorgi & H. Stevenin & S. M. Ratto, 2023. "The use of machine learning techniques for a predictive model of debris flows triggered by short intense rainfall," 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. 117(1), pages 143-162, May.
  55. Siddharth Sethi & David Zhang & Sebastian Guelfi & Zhongbo Chen & Sonia Garcia-Ruiz & Emmanuel O. Olagbaju & Mina Ryten & Harpreet Saini & Juan A. Botia, 2022. "Leveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  56. Takuji Matsumoto & Yuji Yamada, 2021. "Comprehensive and Comparative Analysis of GAM-Based PV Power Forecasting Models Using Multidimensional Tensor Product Splines against Machine Learning Techniques," Energies, MDPI, vol. 14(21), pages 1-22, November.
  57. 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.
  58. Paola Perchinunno & Massimo Bilancia & Domenico Vitale, 2021. "A Statistical Analysis of Factors Affecting Higher Education Dropouts," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 341-362, August.
  59. 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.
  60. Spencer Matthews & Brian Hartman, 2022. "Machine Learning in Ratemaking, an Application in Commercial Auto Insurance," Risks, MDPI, vol. 10(4), pages 1-25, April.
  61. Daifeng Xiang & Gangsheng Wang & Jing Tian & Wanyu Li, 2023. "Global patterns and edaphic-climatic controls of soil carbon decomposition kinetics predicted from incubation experiments," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  62. Noorian, Farzad & de Silva, Anthony M. & Leong, Philip H. W., 2016. "gramEvol: Grammatical Evolution in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 71(i01).
  63. Badih Ghattas & Diane Manzon, 2023. "Machine Learning Alternatives to Response Surface Models," Mathematics, MDPI, vol. 11(15), pages 1-27, August.
  64. Patricia Jimeno-Sáez & Javier Senent-Aparicio & José M. Cecilia & Julio Pérez-Sánchez, 2020. "Using Machine-Learning Algorithms for Eutrophication Modeling: Case Study of Mar Menor Lagoon (Spain)," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
  65. Joel Podgorski & Oliver Kracht & Luis Araguas-Araguas & Stefan Terzer-Wassmuth & Jodie Miller & Ralf Straub & Rolf Kipfer & Michael Berg, 2024. "Groundwater vulnerability to pollution in Africa’s Sahel region," Nature Sustainability, Nature, vol. 7(5), pages 558-567, May.
  66. Yagli, Gokhan Mert & Yang, Dazhi & Srinivasan, Dipti, 2019. "Automatic hourly solar forecasting using machine learning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 487-498.
  67. Anne C. Richer-de-Forges & Dominique Arrouays & Songchao Chen & Zamir Libohova & Dylan E. Beaudette & Hocine Bourennane, 2024. "Mapping Topsoil Behavior to Compaction at National Scale from an Analysis of Field Observations," Land, MDPI, vol. 13(7), pages 1-23, July.
  68. Angel Hsu & Xuewei Wang & Jonas Tan & Wayne Toh & Nihit Goyal, 2022. "Predicting European cities’ climate mitigation performance using machine learning," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  69. Bertrand,Marianne & Crepon,Bruno Jacques Jean Philippe & Marguerie,Alicia Charlene & Premand,Patrick, 2021. "Do Workfare Programs Live Up to Their Promises ? Experimental Evidence from Côte d’Ivoire," Policy Research Working Paper Series 9611, The World Bank.
  70. Bellotti, Anthony & Brigo, Damiano & Gambetti, Paolo & Vrins, Frédéric, 2021. "Forecasting recovery rates on non-performing loans with machine learning," International Journal of Forecasting, Elsevier, vol. 37(1), pages 428-444.
  71. Schmitt, Rafael Jan Pablo & Rosa, Lorenzo, 2024. "Dams for hydropower and irrigation: Trends, challenges, and alternatives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
  72. Jingwei Li & Choon-Ling Sia & Zhuo Chen & Wei Huang, 2021. "Enhancing Influenza Epidemics Forecasting Accuracy in China with Both Official and Unofficial Online News Articles, 2019–2020," IJERPH, MDPI, vol. 18(12), pages 1-13, June.
  73. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
  74. Arellano-García, María Evarista & Camacho-Gutiérrez, José Ariel & Solorza-Calderón, Selene, 2021. "Machine learning approach for higher-order interactions detection to ecological communities management," Applied Mathematics and Computation, Elsevier, vol. 411(C).
  75. Ribeiro, Matheus Henrique Dal Molin & da Silva, Ramon Gomes & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2020. "Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
  76. Ali Soleymani & Frank Pennekamp & Owen L Petchey & Robert Weibel, 2015. "Developing and Integrating Advanced Movement Features Improves Automated Classification of Ciliate Species," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
  77. Makariou, Despoina & Barrieu, Pauline & Chen, Yining, 2021. "A random forest based approach for predicting spreads in the primary catastrophe bond market," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 140-162.
  78. Antonio Rodríguez Andrés & Abraham Otero & Voxi Heinrich Amavilah, 2022. "Knowledge economy classification in African countries: A model-based clustering approach," Information Technology for Development, Taylor & Francis Journals, vol. 28(2), pages 372-396, April.
  79. Yagli, Gokhan Mert & Yang, Dazhi & Gandhi, Oktoviano & Srinivasan, Dipti, 2020. "Can we justify producing univariate machine-learning forecasts with satellite-derived solar irradiance?," Applied Energy, Elsevier, vol. 259(C).
  80. Joel Podgorski & Michael Berg, 2022. "Global analysis and prediction of fluoride in groundwater," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  81. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
  82. Mehmet Güney Celbiş, 2021. "A machine learning approach to rural entrepreneurship," Papers in Regional Science, Wiley Blackwell, vol. 100(4), pages 1079-1104, August.
  83. Soo Ching Lee & Mei San Tang & Alice V Easton & Joseph Cooper Devlin & Ling Ling Chua & Ilseung Cho & Foong Ming Moy & Tsung Fei Khang & Yvonne A L Lim & P’ng Loke, 2019. "Linking the effects of helminth infection, diet and the gut microbiota with human whole-blood signatures," PLOS Pathogens, Public Library of Science, vol. 15(12), pages 1-30, December.
  84. José Antonio Moya, 2017. "Where Diffusion of Clean Technologies and Barriers to Innovation Clash: Application to the Global Diffusion of the Electrical Arc Furnace," Energies, MDPI, vol. 10(1), pages 1-22, January.
  85. Xu, Xu & McGrory, Clare Anne & Wang, You-Gan & Wu, Jinran, 2021. "Influential factors on Chinese airlines’ profitability and forecasting methods," Journal of Air Transport Management, Elsevier, vol. 91(C).
  86. 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.
  87. Nasery, Praanjal & Aziz Ezzat, Ahmed, 2023. "Yaw-adjusted wind power curve modeling: A local regression approach," Renewable Energy, Elsevier, vol. 202(C), pages 1368-1376.
  88. Amit Moscovich & Saharon Rosset, 2022. "On the cross‐validation bias due to unsupervised preprocessing," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1474-1502, September.
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  90. Magboul M. Sulieman & Fuat Kaya & Mohammed A. Elsheikh & Levent Başayiğit & Rosa Francaviglia, 2023. "Application of Machine Learning Algorithms for Digital Mapping of Soil Salinity Levels and Assessing Their Spatial Transferability in Arid Regions," Land, MDPI, vol. 12(9), pages 1-22, August.
  91. Hokuto Nakata & Akifumi Eguchi & Shouta M. M. Nakayama & John Yabe & Kaampwe Muzandu & Yoshinori Ikenaka & Chisato Mori & Mayumi Ishizuka, 2022. "Metabolomic Alteration in the Plasma of Wild Rodents Environmentally Exposed to Lead: A Preliminary Study," IJERPH, MDPI, vol. 19(1), pages 1-14, January.
  92. Hamid Reza Pourghasemi & Nitheshnirmal Sadhasivam & Mahdis Amiri & Saeedeh Eskandari & M. Santosh, 2021. "Landslide susceptibility assessment and mapping using state-of-the art machine learning techniques," 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. 108(1), pages 1291-1316, August.
  93. Jack S. Gisby & Norzawani B. Buang & Artemis Papadaki & Candice L. Clarke & Talat H. Malik & Nicholas Medjeral-Thomas & Damiola Pinheiro & Paige M. Mortimer & Shanice Lewis & Eleanor Sandhu & Stephen , 2022. "Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
  94. Tobias Rentschler & Philipp Gries & Thorsten Behrens & Helge Bruelheide & Peter Kühn & Steffen Seitz & Xuezheng Shi & Stefan Trogisch & Thomas Scholten & Karsten Schmidt, 2019. "Comparison of catchment scale 3D and 2.5D modelling of soil organic carbon stocks in Jiangxi Province, PR China," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-23, August.
  95. Michimasa Fujiogi & Yoshihiko Raita & Marcos Pérez-Losada & Robert J. Freishtat & Juan C. Celedón & Jonathan M. Mansbach & Pedro A. Piedra & Zhaozhong Zhu & Carlos A. Camargo & Kohei Hasegawa, 2022. "Integrated relationship of nasopharyngeal airway host response and microbiome associates with bronchiolitis severity," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  96. Arjan S. Gosal & Janine A. McMahon & Katharine M. Bowgen & Catherine H. Hoppe & Guy Ziv, 2021. "Identifying and Mapping Groups of Protected Area Visitors by Environmental Awareness," Land, MDPI, vol. 10(6), pages 1-14, May.
  97. Gehan A. Mousa & Elsayed A. H. Elamir & Khaled Hussainey, 2022. "Using machine learning methods to predict financial performance: Does disclosure tone matter?," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 19(1), pages 93-112, March.
  98. Hye-Ryeong Nam & Seo-Hoon Kim & Seol-Yee Han & Sung-Jin Lee & Won-Hwa Hong & Jong-Hun Kim, 2020. "Statistical Methodology for the Definition of Standard Model for Energy Analysis of Residential Buildings in Korea," Energies, MDPI, vol. 13(21), pages 1-16, November.
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