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The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

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Cited by:

  1. Matthew Smith & Francisco Alvarez, 2022. "Predicting Firm-Level Bankruptcy in the Spanish Economy Using Extreme Gradient Boosting," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 263-295, January.
  2. Gavoille, Nicolas & Zasova, Anna, 2023. "What we pay in the shadows: Labor tax evasion, minimum wage hike and employment," Journal of Public Economics, Elsevier, vol. 228(C).
  3. Ke Wang & Qingwen Xue & Jian John Lu, 2021. "Risky Driver Recognition with Class Imbalance Data and Automated Machine Learning Framework," IJERPH, MDPI, vol. 18(14), pages 1-18, July.
  4. Bouvatier, Vincent & El Ouardi, Sofiane, 2023. "Credit gaps as banking crisis predictors: A different tune for middle- and low-income countries," Emerging Markets Review, Elsevier, vol. 54(C).
  5. Matthieu Garcin & Samuel Stéphan, 2023. "Credit scoring using neural networks and SURE posterior probability calibration," Working Papers hal-03286760, HAL.
  6. Mohamed Zul Fadhli Khairuddin & Puat Lu Hui & Khairunnisa Hasikin & Nasrul Anuar Abd Razak & Khin Wee Lai & Ahmad Shakir Mohd Saudi & Siti Salwa Ibrahim, 2022. "Occupational Injury Risk Mitigation: Machine Learning Approach and Feature Optimization for Smart Workplace Surveillance," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
  7. Zhenghui Sha & Yun Huang & Jiawei Sophia Fu & Mingxian Wang & Yan Fu & Noshir Contractor & Wei Chen, 2018. "A Network-Based Approach to Modeling and Predicting Product Coconsideration Relations," Complexity, Hindawi, vol. 2018, pages 1-14, January.
  8. Amanda Fitzgerald & Naoise Mac Giollabhui & Louise Dolphin & Robert Whelan & Barbara Dooley, 2018. "Dissociable psychosocial profiles of adolescent substance users," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-16, August.
  9. Onur Coskun & Alper Aldemir, 2023. "Machine learning network suitable for accurate rapid seismic risk estimation of masonry building stocks," 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. 115(1), pages 261-287, January.
  10. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
  11. Gallego, Jorge & Rivero, Gonzalo & Martínez, Juan, 2021. "Preventing rather than punishing: An early warning model of malfeasance in public procurement," International Journal of Forecasting, Elsevier, vol. 37(1), pages 360-377.
  12. Álvarez-Diez, Susana & Baixauli-Soler, J. Samuel & Lozano-Reina, Gabriel & Rodríguez-Linares Rey, Diego, 2024. "Subsidies for investing in energy efficiency measures: Applying a random forest model for unbalanced samples," Applied Energy, Elsevier, vol. 359(C).
  13. Maud Thomas & Holger Rootzén, 2022. "Real‐time prediction of severe influenza epidemics using extreme value statistics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(2), pages 376-394, March.
  14. Marco Due~nas & Federico Nutarelli & V'ictor Ortiz & Massimo Riccaboni & Francesco Serti, 2021. "Assessing the Heterogeneous Impact of Economy-Wide Shocks: A Machine Learning Approach Applied to Colombian Firms," Papers 2104.04570, arXiv.org, revised Nov 2024.
  15. Chen, Jian & Katchova, Ani L. & Zhou, Chenxi, 2021. "Agricultural loan delinquency prediction using machine learning methods," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 24(5), May.
  16. Gao, Wei & Ju, Ming & Yang, Tongyang, 2023. "Severe weather and peer-to-peer farmers’ loan default predictions: Evidence from machine learning analysis," Finance Research Letters, Elsevier, vol. 58(PA).
  17. Rummens, Anneleen & Hardyns, Wim, 2021. "The effect of spatiotemporal resolution on predictive policing model performance," International Journal of Forecasting, Elsevier, vol. 37(1), pages 125-133.
  18. Jie-Huei Wang & Cheng-Yu Liu & You-Ruei Min & Zih-Han Wu & Po-Lin Hou, 2024. "Cancer Diagnosis by Gene-Environment Interactions via Combination of SMOTE-Tomek and Overlapped Group Screening Approaches with Application to Imbalanced TCGA Clinical and Genomic Data," Mathematics, MDPI, vol. 12(14), pages 1-24, July.
  19. Le, Hong Hanh & Viviani, Jean-Laurent, 2018. "Predicting bank failure: An improvement by implementing a machine-learning approach to classical financial ratios," Research in International Business and Finance, Elsevier, vol. 44(C), pages 16-25.
  20. Xu-Wen Wang & Lorenzo Madeddu & Kerstin Spirohn & Leonardo Martini & Adriano Fazzone & Luca Becchetti & Thomas P. Wytock & István A. Kovács & Olivér M. Balogh & Bettina Benczik & Mátyás Pétervári & Be, 2023. "Assessment of community efforts to advance network-based prediction of protein–protein interactions," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  21. Kumar, Ajay & Singh, Shashank Sheshar & Singh, Kuldeep & Biswas, Bhaskar, 2020. "Link prediction techniques, applications, and performance: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
  22. Soyoung Oh & Honggeun Ji & Jina Kim & Eunil Park & Angel P. del Pobil, 2022. "Deep learning model based on expectation-confirmation theory to predict customer satisfaction in hospitality service," Information Technology & Tourism, Springer, vol. 24(1), pages 109-126, March.
  23. John Muschelli, 2020. "ROC and AUC with a Binary Predictor: a Potentially Misleading Metric," Journal of Classification, Springer;The Classification Society, vol. 37(3), pages 696-708, October.
  24. João Chang Junior & Fábio Binuesa & Luiz Fernando Caneo & Aida Luiza Ribeiro Turquetto & Elisandra Cristina Trevisan Calvo Arita & Aline Cristina Barbosa & Alfredo Manoel da Silva Fernandes & Evelinda, 2020. "Improving preoperative risk-of-death prediction in surgery congenital heart defects using artificial intelligence model: A pilot study," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-21, September.
  25. Aziemah Azhar & Noratiqah Mohd Ariff & Mohd Aftar Abu Bakar & Azzuhana Roslan, 2022. "Classification of Driver Injury Severity for Accidents Involving Heavy Vehicles with Decision Tree and Random Forest," Sustainability, MDPI, vol. 14(7), pages 1-19, March.
  26. Alfred Krzywicki & David Muchlinski & Benjamin E. Goldsmith & Arcot Sowmya, 2022. "From academia to policy makers: a methodology for real-time forecasting of infrequent events," Journal of Computational Social Science, Springer, vol. 5(2), pages 1489-1510, November.
  27. Wei-Hsuan Lo-Ciganic & Julie M Donohue & Eric G Hulsey & Susan Barnes & Yuan Li & Courtney C Kuza & Qingnan Yang & Jeanine Buchanich & James L Huang & Christina Mair & Debbie L Wilson & Walid F Gellad, 2021. "Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-18, March.
  28. De Souter Luna, 2024. "Evaluating Boolean relationships in Configurational Comparative Methods," Journal of Causal Inference, De Gruyter, vol. 12(1), pages 1-25, January.
  29. Arthur De Sá Ferreira & Ney Meziat-Filho & Ana Paula Antunes Ferreira, 2021. "Double threshold receiver operating characteristic plot for three-modal continuous predictors," Computational Statistics, Springer, vol. 36(3), pages 2231-2245, September.
  30. Jeong-Cheol Kim & Sunmin Lee, 2023. "Comparative Study of Deep Neural Networks for Landslide Susceptibility Assessment: A Case Study of Pyeongchang-gun, South Korea," Sustainability, MDPI, vol. 16(1), pages 1-13, December.
  31. Montorsi, Carlotta & Fusco, Alessio & Van Kerm, Philippe & Bordas, Stéphane P.A., 2024. "Predicting depression in old age: Combining life course data with machine learning," Economics & Human Biology, Elsevier, vol. 52(C).
  32. Nica-Avram, Georgiana & Harvey, John & Smith, Gavin & Smith, Andrew & Goulding, James, 2021. "Identifying food insecurity in food sharing networks via machine learning," Journal of Business Research, Elsevier, vol. 131(C), pages 469-484.
  33. Malka N. Halgamuge, 2020. "Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells," IJERPH, MDPI, vol. 17(12), pages 1-27, June.
  34. Ali J. Ghandour & Huda Hammoud & Samar Al-Hajj, 2020. "Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach," IJERPH, MDPI, vol. 17(11), pages 1-13, June.
  35. Zeyu Liu & Anahita Khojandi & Xueping Li & Akram Mohammed & Robert L Davis & Rishikesan Kamaleswaran, 2022. "A Machine Learning–Enabled Partially Observable Markov Decision Process Framework for Early Sepsis Prediction," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 2039-2057, July.
  36. Fan, Xudong & Wang, Xiaowei & Zhang, Xijin & ASCE Xiong (Bill) Yu, P.E.F., 2022. "Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
  37. Peter Ebbes & Oded Netzer, 2022. "Using Social Network Activity Data to Identify and Target Job Seekers," Management Science, INFORMS, vol. 68(4), pages 3026-3046, April.
  38. Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.
  39. Derek Ka-Hei Lai & Ethan Shiu-Wang Cheng & Bryan Pak-Hei So & Ye-Jiao Mao & Sophia Ming-Yan Cheung & Daphne Sze Ki Cheung & Duo Wai-Chi Wong & James Chung-Wai Cheung, 2023. "Transformer Models and Convolutional Networks with Different Activation Functions for Swallow Classification Using Depth Video Data," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
  40. Falco J. Bargagli-Dtoffi & Massimo Riccaboni & Armando Rungi, 2020. "Machine Learning for Zombie Hunting. Firms Failures and Financial Constraints," Working Papers 01/2020, IMT School for Advanced Studies Lucca, revised Jun 2020.
  41. Jiyoung Song & Young Chul Lee & Jeongsu Lee, 2023. "Deep generative model with time series-image encoding for manufacturing fault detection in die casting process," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 3001-3014, October.
  42. Dueñas, Marco & Ortiz, Víctor & Riccaboni, Massimo & Serti, Francesco, 2021. "Assessing the Impact of COVID-19 on Trade: a Machine Learning Counterfactual Analysis," Working papers 79, Red Investigadores de Economía.
  43. Zhang, Han, 2021. "How Using Machine Learning Classification as a Variable in Regression Leads to Attenuation Bias and What to Do About It," SocArXiv 453jk, Center for Open Science.
  44. Merlijn Breugel & Cancan Qi & Zhongli Xu & Casper-Emil T. Pedersen & Ilya Petoukhov & Judith M. Vonk & Ulrike Gehring & Marijn Berg & Marnix Bügel & Orestes A. Carpaij & Erick Forno & Andréanne Morin , 2022. "Nasal DNA methylation at three CpG sites predicts childhood allergic disease," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  45. Jara-Arriagada, Carlos & Stoianov, Ivan, 2021. "Pipe breaks and estimating the impact of pressure control in water supply networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
  46. Zaghloul, Maha & Barakat, Sherif & Rezk, Amira, 2024. "Predicting E-commerce customer satisfaction: Traditional machine learning vs. deep learning approaches," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
  47. Song, Kwonsik & Anderson, Kyle & Lee, SangHyun, 2020. "An energy-cyber-physical system for personalized normative messaging interventions: Identification and classification of behavioral reference groups," Applied Energy, Elsevier, vol. 260(C).
  48. Jianyuan Deng & Zhibo Yang & Hehe Wang & Iwao Ojima & Dimitris Samaras & Fusheng Wang, 2023. "A systematic study of key elements underlying molecular property prediction," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
  49. Kwanda Sydwell Ngwenduna & Rendani Mbuvha, 2021. "Alleviating Class Imbalance in Actuarial Applications Using Generative Adversarial Networks," Risks, MDPI, vol. 9(3), pages 1-33, March.
  50. Falco J. Bargagli-Stoffi & Fabio Incerti & Massimo Riccaboni & Armando Rungi, 2023. "Machine Learning for Zombie Hunting: Predicting Distress from Firms' Accounts and Missing Values," Papers 2306.08165, arXiv.org.
  51. Amirhossein Salimi & Amir Noori & Isa Ebtehaj & Tadros Ghobrial & Hossein Bonakdari, 2024. "Advancing Spatial Drought Forecasts by Integrating an Improved Outlier Robust Extreme Learning Machine with Gridded Data: A Case Study of the Lower Mainland Basin, British Columbia, Canada," Sustainability, MDPI, vol. 16(8), pages 1-27, April.
  52. Zhichao Yang & Avijit Mitra & Weisong Liu & Dan Berlowitz & Hong Yu, 2023. "TransformEHR: transformer-based encoder-decoder generative model to enhance prediction of disease outcomes using electronic health records," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  53. Fisnik Doko & Slobodan Kalajdziski & Igor Mishkovski, 2021. "Credit Risk Model Based on Central Bank Credit Registry Data," JRFM, MDPI, vol. 14(3), pages 1-17, March.
  54. Kajal Lahiri & Cheng Yang, 2023. "ROC and PRC Approaches to Evaluate Recession Forecasts," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 19(2), pages 119-148, September.
  55. Gustavo Balbinot & Guijin Li & Sukhvinder Kalsi-Ryan & Rainer Abel & Doris Maier & Yorck-Bernhard Kalke & Norbert Weidner & Rüdiger Rupp & Martin Schubert & Armin Curt & Jose Zariffa, 2023. "Segmental motor recovery after cervical spinal cord injury relates to density and integrity of corticospinal tract projections," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  56. Amolika Sinha & Vincent Vu & Sai Chand & Kasun Wijayaratna & Vinayak Dixit, 2021. "A Crash Injury Model Involving Autonomous Vehicle: Investigating of Crash and Disengagement Reports," Sustainability, MDPI, vol. 13(14), pages 1-22, July.
  57. Ke Wang & Qingwen Xue & Yingying Xing & Chongyi Li, 2020. "Improve Aggressive Driver Recognition Using Collision Surrogate Measurement and Imbalanced Class Boosting," IJERPH, MDPI, vol. 17(7), pages 1-17, March.
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