1.N. V. Chawla, K. W. Bowyer, L. O. Hall, W. P. Kegelmeyer. (2002). SMOTE: Synthetic Minority Over-sampling Technique. Journal of Artificial Intelligence Research, 16, 321–357[10.1613/jair.953]
2.Arthur Asuncion. (2007). UCI Machine Learning Repository. Medical Entomology and Zoology
3.Glenn Shafer. (2020). A Mathematical Theory of Evidence. Princeton University Press eBooks[10.2307/j.ctv10vm1qb]
4.John A. Swets. (1988). Measuring the Accuracy of Diagnostic Systems. Science, 240(4857), 1285–1293[10.1126/science.3287615]
5.Glenn Shafer. (1976). A Mathematical Theory of Evidence. Princeton University Press eBooks[10.1515/9780691214696]
6.Geoffrey McLachlan, David Peel. (2000). Finite Mixture Models. Wiley series in probability and statistics, 6(1), 355–378[10.1002/0471721182]
7.Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael Steinbach, David J. Hand, Dan Steinberg. (2007). Top 10 algorithms in data mining. Knowledge and Information Systems, 14(1), 1–37[10.1007/s10115-007-0114-2]
8.Evelyn Fix, J. L. Hodges. (1989). Discriminatory Analysis. Nonparametric Discrimination: Consistency Properties. International Statistical Review, 57(3), 238[10.2307/1403797]
9.Jesús Alcalá‐Fdez, Alberto Fernández, Julián Luengo, J. Derrac, Salvador García, Luciano Sánchez, Francisco Herrera. (2011). KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. , 17, 255–287
10.Sahibsingh A. Dudani. (1976). The Distance-Weighted k-Nearest-Neighbor Rule. IEEE Transactions on Systems Man and Cybernetics, SMC-6(4), 325–327[10.1109/tsmc.1976.5408784]
11.T. Denoeux. (1995). A k-nearest neighbor classification rule based on Dempster-Shafer theory. IEEE Transactions on Systems Man and Cybernetics, 25(5), 804–813[10.1109/21.376493]
12.QIANG YANG, XINDONG WU. (2006). 10 CHALLENGING PROBLEMS IN DATA MINING RESEARCH. International Journal of Information Technology & Decision Making, 05(04), 597–604[10.1142/s0219622006002258]
13.Thierry Denœux. (2008). A k-Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory. Studies in fuzziness and soft computing, 737–760[10.1007/978-3-540-44792-4_29]
14.Jianping Gou, Hongxing Ma, Weihua Ou, Shaoning Zeng, Yunbo Rao, Hebiao Yang. (2018). A generalized mean distance-based k-nearest neighbor classifier. Expert Systems with Applications, 115, 356–372[10.1016/j.eswa.2018.08.021]
15.David A. Cieslak, Nitesh V. Chawla. (2008). Learning Decision Trees for Unbalanced Data. Lecture notes in computer science, 241–256[10.1007/978-3-540-87479-9_34]
16.Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V. Chawla. (2010). A Robust Decision Tree Algorithm for Imbalanced Data Sets. , 766–777[10.1137/1.9781611972801.67]
17.Wei Liu, Sanjay Chawla. (2011). Class Confidence Weighted kNN Algorithms for Imbalanced Data Sets. Lecture notes in computer science, 345–356[10.1007/978-3-642-20847-8_29]
18.Yuxuan Li, Xiuzhen Zhang. (2011). Improving k Nearest Neighbor with Exemplar Generalization for Imbalanced Classification. Lecture notes in computer science, 321–332[10.1007/978-3-642-20847-8_27]
19.Harshit Dubey, Vikram Pudi. (2013). Class Based Weighted K-Nearest Neighbor over Imbalance Dataset. Lecture notes in computer science, 305–316[10.1007/978-3-642-37456-2_26]
20.Pritom Saha Akash, Md. Eusha Kadir, Amin Ahsan Ali, Mohammad Shoyaib. (2019). Inter-node Hellinger Distance based Decision Tree. , 1967–1973[10.24963/ijcai.2019/272]
21.Theodore B. Trafalis, Samir A. Alwazzi. (2007). Support vector regression with noisy data: a second order cone programming approach. International Journal of General Systems, 36(2), 237–250[10.1080/03081070601058760]
22.Evelyn Fix, J. L. Hodges. (1951). Discriminatory analysis: Nonparametric discrimination: Consistency properties. PsycEXTRA Dataset[10.1037/e471672008-001]
Cited By
1.Marcio Dorn, Bruno Iochins Grisci, Pedro Henrique Narloch, Bruno César Feltes, Eduardo Avila, Alessandro Kahmann, Clarice Sampaio Alho. (2021). Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets. PeerJ Computer Science, 7, e670[10.7717/peerj-cs.670]
2.Ali Fazli, Javad Poshtan. (2024). Wind turbine fault detection and isolation robust against data imbalance using KNN. Energy Science & Engineering, 12(3), 1174–1186[10.1002/ese3.1706]
3.Md Nazmul Haque, Sadia Sharmin, Amin Ahsan Ali, Abu Ashfaqur Sajib, Mohammad Shoyaib. (2021). Use of relevancy and complementary information for discriminatory gene selection from high-dimensional gene expression data. PLoS ONE, 16(10), e0230164[10.1371/journal.pone.0230164]
4.Suravi Akhter, Sadia Sharmin, Sumon Ahmed, Abu Ashfaqur Sajib, Mohammad Shoyaib. (2021). mRelief: A Reward Penalty Based Feature Subset Selection Considering Data Overlapping Problem. Lecture notes in computer science, 278–292[10.1007/978-3-030-77961-0_24]
5.Md. Hasan Tarek, Md. Mumtahin Habib Ullah Mazumder, Sadia Sharmin, Md. Shariful Islam, Mohammad Shoyaib, Muhammad Mahbub Alam. (2022). RHC: Cluster based Feature Reduction for Network Intrusion Detections. , 15, 378–384[10.1109/ccnc49033.2022.9700680]
6.Pablo Ormeño, Gastón Márquez, Carla Taramasco. (2024). Evaluation of Machine Learning Techniques for Classifying and Balancing Data on an Unbalanced Mini-Mental State Examination Test Data Collection Applied in Chile. IEEE Access, 12, 49376–49386[10.1109/access.2024.3383837]
7.Hüseyin Ünlü, Ozan Raşit Yürüm, Ali Yıldız, Onur Demirörs. (2024). Application of a Size Measurement Standard for Data Warehouse Projects. Software Practice and Experience, 55(3), 571–588[10.1002/spe.3391]
8.Arnab Mukherjee, Md. Zahidul Islam Islam, Lasker Ershad Ali. (2024). Human iris classification through Histogram of Oriented Gradient features with various distance metrics. Machine Graphics and Vision, 33(3/4), 97–124[10.22630/mgv.2024.33.3.5]
9.Bidyapati Thiyam, Chadalavada Suptha Saranya, Shouvik Dey. (2024). Class‐Imbalanced Problems in Malware Analysis and Detection in Classification Algorithms. , 61–81[10.1002/9781394230600.ch4]
10.Anh Hoang, Toan Nguyen Mau, Van-Nam Huynh. (2021). Mass-Based Similarity Weighted k-Neighbor for Class Imbalance. Lecture notes in computer science, 143–155[10.1007/978-3-030-85529-1_12]
11.Tom Wilson, Samuel Wisdish, Josh Osofa, Dominic J. Farris. (2025). Evaluating Machine Learning-Based Classification of Human Locomotor Activities for Exoskeleton Control Using Inertial Measurement Unit and Pressure Insole Data. Sensors, 25(17), 5365[10.3390/s25175365]
12.(2021). Peer Review #1 of "Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets (v0.2)". [10.7287/peerj-cs.670v0.2/reviews/1]
13.Dina Shehada, Suadad Muammar, Maryam Ali Amour, Ahmed Bouridane. (2023). Investigating The Impact of Sampling Techniques on an Imbalanced Classification Problem. , 39–44[10.1109/icspis60075.2023.10344073]
14.(2021). Peer Review #3 of "Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets (v0.1)". [10.7287/peerj-cs.670v0.1/reviews/3]
15.(2021). Peer Review #1 of "Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets (v0.1)". [10.7287/peerj-cs.670v0.1/reviews/1]
16.(2021). Peer Review #3 of "Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets (v0.2)". [10.7287/peerj-cs.670v0.2/reviews/3]
17.Peter Domjan, Viola Angyal, Adam Bertalan, Istvan Vingender, Elek Dinya. (2025). A New Bayesian Approach to Increase Measurement Accuracy Using a Precision Entropy Indicator. Research Square[10.21203/rs.3.rs-5926277/v1]
18.Md. Eusha Kadir, Md. Mumtahin Habib Ullah Mazumder, Muhammad Mahbub Alam, Mohammad Shoyaib. (2026). An Evidential Dynamic Neighborhood Approach to Learn from Imbalanced Data. Annals of Data Science[10.1007/s40745-026-00709-0]
19.P Gonzalez-Dias. (2021). Peer Review #2 of "Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets (v0.2)". [10.7287/peerj-cs.670v0.2/reviews/2]