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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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  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. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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).
  11. 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.
  12. 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.
  13. 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.
  14. 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).
  15. 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.
  16. 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.
  17. De Souter Luna, 2024. "Evaluating Boolean relationships in Configurational Comparative Methods," Journal of Causal Inference, De Gruyter, vol. 12(1), pages 1-25, January.
  18. 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.
  19. 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.
  20. 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).
  21. 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.
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  23. 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.
  24. 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).
  25. 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.
  26. 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.
  27. 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.
  28. 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).
  29. 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.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. Abouelmagd THM, 2018. "A New Flexible Distribution Based on the Zero Truncated Poisson Distribution: Mathematical Properties and Applications to Lifetime Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 8(1), pages 10-16, August.
  35. Massimiliano Fessina & Giambattista Albora & Andrea Tacchella & Andrea Zaccaria, 2022. "Which products activate a product? An explainable machine learning approach," Papers 2212.03094, arXiv.org.
  36. Masabho P Milali & Samson S Kiware & Nicodem J Govella & Fredros Okumu & Naveen Bansal & Serdar Bozdag & Jacques D Charlwood & Marta F Maia & Sheila B Ogoma & Floyd E Dowell & George F Corliss & Maggy, 2020. "An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.
  37. Daniel R Jeske, 2018. "Metrics Used When Evaluating the Performance of Statistical Classifiers," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 8(1), pages 7-9, August.
  38. Islam, Towhidul & Meade, Nigel & Carson, Richard T. & Louviere, Jordan J. & Wang, Juan, 2022. "The usefulness of socio-demographic variables in predicting purchase decisions: Evidence from machine learning procedures," Journal of Business Research, Elsevier, vol. 151(C), pages 324-338.
  39. Alex Hawkins-Hooker & Giovanni Visonà & Tanmayee Narendra & Mateo Rojas-Carulla & Bernhard Schölkopf & Gabriele Schweikert, 2023. "Getting personal with epigenetics: towards individual-specific epigenomic imputation with machine learning," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  40. Lea Helmers & Franziska Horn & Franziska Biegler & Tim Oppermann & Klaus-Robert Müller, 2019. "Automating the search for a patent’s prior art with a full text similarity search," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-17, March.
  41. van Weezel, Stijn, 2020. "Local warming and violent armed conflict in Africa," World Development, Elsevier, vol. 126(C).
  42. Matthieu Garcin & Samuel St'ephan, 2021. "Credit scoring using neural networks and SURE posterior probability calibration," Papers 2107.07206, arXiv.org.
  43. St'ephane Cr'epey & Lehdili Noureddine & Nisrine Madhar & Maud Thomas, 2022. "Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural Networks," Papers 2209.11686, arXiv.org, revised Oct 2022.
  44. Ruosha Li & Jing Ning & Ziding Feng, 2022. "Estimation and inference of predictive discrimination for survival outcome risk prediction models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(2), pages 219-240, April.
  45. Sérgio Dias & Tiago Simões & Francisco Fernandes & Ana Mafalda Martins & Alfredo Ferreira & Joaquim Jorge & Abel J P Gomes, 2019. "CavBench: A benchmark for protein cavity detection methods," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-16, October.
  46. Juliet Chebet Moso & Stéphane Cormier & Cyril de Runz & Hacène Fouchal & John Mwangi Wandeto, 2021. "Anomaly Detection on Data Streams for Smart Agriculture," Agriculture, MDPI, vol. 11(11), pages 1-17, November.
  47. Florian, Eleonora & Sgarbossa, Fabio & Zennaro, Ilenia, 2021. "Machine learning-based predictive maintenance: A cost-oriented model for implementation," International Journal of Production Economics, Elsevier, vol. 236(C).
  48. Faith M. Hartley & Aaron E. Maxwell & Rick E. Landenberger & Zachary J. Bortolot, 2022. "Forest Type Differentiation Using GLAD Phenology Metrics, Land Surface Parameters, and Machine Learning," Geographies, MDPI, vol. 2(3), pages 1-25, August.
  49. Tzu-Hsuan Lin & Jehn-Ruey Jiang, 2021. "Credit Card Fraud Detection with Autoencoder and Probabilistic Random Forest," Mathematics, MDPI, vol. 9(21), pages 1-16, October.
  50. Robert A. Blair & Nicholas Sambanis, 2021. "Is Theory Useful for Conflict Prediction? A Response to Beger, Morgan, and Ward," Journal of Conflict Resolution, Peace Science Society (International), vol. 65(7-8), pages 1427-1453, August.
  51. Mieke Deschepper & Willem Waegeman & Dirk Vogelaers & Kristof Eeckloo, 2020. "Using structured pathology data to predict hospital-wide mortality at admission," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-11, June.
  52. Artur Sokolovsky & Luca Arnaboldi & Jaume Bacardit & Thomas Gross, 2021. "Volume-Centred Range Bars: Novel Interpretable Representation of Financial Markets Designed for Machine Learning Applications," Papers 2103.12419, arXiv.org, revised May 2022.
  53. Sergio Picart-Armada & Steven J Barrett & David R Willé & Alexandre Perera-Lluna & Alex Gutteridge & Benoit H Dessailly, 2019. "Benchmarking network propagation methods for disease gene identification," PLOS Computational Biology, Public Library of Science, vol. 15(9), pages 1-24, September.
  54. Bouvatier, Vincent & Lepetit, Laetitia & Rehault, Pierre-Nicolas & Strobel, Frank, 2023. "Time-varying Z-score measures for bank insolvency risk: Best practice," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 170-179.
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  57. 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.
  58. 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).
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