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Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric

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  1. Mirza Rizwan Sajid & Bader A. Almehmadi & Waqas Sami & Mansour K. Alzahrani & Noryanti Muhammad & Christophe Chesneau & Asif Hanif & Arshad Ali Khan & Ahmad Shahbaz, 2021. "Development of Nonlaboratory-Based Risk Prediction Models for Cardiovascular Diseases Using Conventional and Machine Learning Approaches," IJERPH, MDPI, vol. 18(23), pages 1-16, November.
  2. Shaniel Chotkan & Raymond van der Meij & Wouter Jan Klerk & Phil J. Vardon & Juan Pablo Aguilar-López, 2022. "A Data-Driven Method for Identifying Drought-Induced Crack-Prone Levees Based on Decision Trees," Sustainability, MDPI, vol. 14(11), pages 1-23, June.
  3. Bruno Faria & Fernao Vistulo de Abreu, 2019. "Cellular frustration algorithms for anomaly detection applications," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-31, July.
  4. Migut Grzegorz, 2020. "Assessment of the Influence of Dependent Variable Distribution on Selected Goodness of Fit Measures Using the Example of Customer Churn Model," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 24(1), pages 51-70, March.
  5. Yash Raj Shrestha & Vivianna Fang He & Phanish Puranam & Georg von Krogh, 2021. "Algorithm Supported Induction for Building Theory: How Can We Use Prediction Models to Theorize?," Organization Science, INFORMS, vol. 32(3), pages 856-880, May.
  6. David Cemernek & Sandra Cemernek & Heimo Gursch & Ashwini Pandeshwar & Thomas Leitner & Matthias Berger & Gerald Klösch & Roman Kern, 2022. "Machine learning in continuous casting of steel: a state-of-the-art survey," Journal of Intelligent Manufacturing, Springer, vol. 33(6), pages 1561-1579, August.
  7. Schade, Philipp & Schuhmacher, Monika C., 2023. "Predicting entrepreneurial activity using machine learning," Journal of Business Venturing Insights, Elsevier, vol. 19(C).
  8. Kouadri, Abdelmalek & Hajji, Mansour & Harkat, Mohamed-Faouzi & Abodayeh, Kamaleldin & Mansouri, Majdi & Nounou, Hazem & Nounou, Mohamed, 2020. "Hidden Markov model based principal component analysis for intelligent fault diagnosis of wind energy converter systems," Renewable Energy, Elsevier, vol. 150(C), pages 598-606.
  9. Ruchika Malhotra & Megha Khanna, 2023. "On the applicability of search-based algorithms for software change prediction," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 55-73, February.
  10. López-Díaz, María Concepción & López-Díaz, Miguel & Martínez-Fernández, Sergio, 2023. "On the optimal binary classifier with an application," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).
  11. Petter Jakobsen & Enrique Garcia-Ceja & Michael Riegler & Lena Antonsen Stabell & Tine Nordgreen & Jim Torresen & Ole Bernt Fasmer & Ketil Joachim Oedegaard, 2020. "Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-16, August.
  12. Zhou, Xiaoyi & Lu, Pan & Zheng, Zijian & Tolliver, Denver & Keramati, Amin, 2020. "Accident Prediction Accuracy Assessment for Highway-Rail Grade Crossings Using Random Forest Algorithm Compared with Decision Tree," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
  13. Nader Mahmoudi & Łukasz P. Olech & Paul Docherty, 2022. "A comprehensive study of domain-specific emoji meanings in sentiment classification," Computational Management Science, Springer, vol. 19(2), pages 159-197, June.
  14. Christian Kauten & Ashish Gupta & Xiao Qin & Glenn Richey, 2022. "Predicting Blood Donors Using Machine Learning Techniques," Information Systems Frontiers, Springer, vol. 24(5), pages 1547-1562, October.
  15. Manuel Casal-Guisande & Jorge Cerqueiro-Pequeño & José-Benito Bouza-Rodríguez & Alberto Comesaña-Campos, 2023. "Integration of the Wang & Mendel Algorithm into the Application of Fuzzy Expert Systems to Intelligent Clinical Decision Support Systems," Mathematics, MDPI, vol. 11(11), pages 1-33, May.
  16. Wang, Xinlin & Yao, Zhihao & Papaefthymiou, Marios, 2023. "A real-time electrical load forecasting and unsupervised anomaly detection framework," Applied Energy, Elsevier, vol. 330(PA).
  17. Wang, Delu & Tong, Xian & Wang, Yadong, 2020. "An early risk warning system for Outward Foreign Direct Investment in Mineral Resource-based enterprises using multi-classifiers fusion," Resources Policy, Elsevier, vol. 66(C).
  18. Salvatore Carta & Alessandro Sebastian Podda & Diego Reforgiato Recupero & Roberto Saia, 2020. "A Local Feature Engineering Strategy to Improve Network Anomaly Detection," Future Internet, MDPI, vol. 12(10), pages 1-30, October.
  19. Bikeri Adline & Kazushi Ikeda, 2023. "A Hawkes Model Approach to Modeling Price Spikes in the Japanese Electricity Market," Energies, MDPI, vol. 16(4), pages 1-20, February.
  20. Faizal Hafiz & Jan Broekaert & Davide La Torre & Akshya Swain, 2021. "A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting," Papers 2111.08060, arXiv.org.
  21. Li, Yang & Zhang, Meng & Chen, Chen, 2022. "A Deep-Learning intelligent system incorporating data augmentation for Short-Term voltage stability assessment of power systems," Applied Energy, Elsevier, vol. 308(C).
  22. Tan Kai Noel Quah & Yi Wei Daniel Tay & Jian Hui Lim & Ming Jen Tan & Teck Neng Wong & King Ho Holden Li, 2023. "Concrete 3D Printing: Process Parameters for Process Control, Monitoring and Diagnosis in Automation and Construction," Mathematics, MDPI, vol. 11(6), pages 1-34, March.
  23. Gnekpe, Christian & Tchuente, Dieudonné & Nyawa, Serge & Dey, Prasanta Kumar, 2024. "Energy Performance of Building Refurbishments: Predictive and Prescriptive AI-based Machine Learning Approaches," Journal of Business Research, Elsevier, vol. 183(C).
  24. Fatemi Bushehri, Seyyed Mohammad Mehdi & Dehghan Khavari, Saeed & Mirjalili, Seyed Hossein & Babaei Meybodi, Hamid & Sardari Zarchi, Mohsen, 2022. "Energy Consumption Prediction in Iran: A Hybrid Machine Learning and Genetic Algorithm Method with Sustainable Development Considerations," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 6(2).
  25. Sermet Pekin & Aykut Sengul, 2024. "The Good, the Better and the Challenging:Insights into Predicting High-Growth Firms using Machine Learning," Working Papers 2413, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  26. Manuel Casal-Guisande & María Torres-Durán & Mar Mosteiro-Añón & Jorge Cerqueiro-Pequeño & José-Benito Bouza-Rodríguez & Alberto Fernández-Villar & Alberto Comesaña-Campos, 2023. "Design and Conceptual Proposal of an Intelligent Clinical Decision Support System for the Diagnosis of Suspicious Obstructive Sleep Apnea Patients from Health Profile," IJERPH, MDPI, vol. 20(4), pages 1-31, February.
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