Weighted K-nearest neighbors classification based on Whale optimization algorithm

[1]  A. A. Aburomman, M. B. I. Reaz,  A novel SVM-KNN-PSO ensemble method for intrusion detection system, Applied Soft Computing,  38 (2016), 360-372.

[2] S. Bandaru, A. H. Ng,  K. Deb, Data mining methods for knowledge discovery in multi-objective optimization: Part A-survey, Expert Systems with Applications, 70 (2017), 139-159.

[3] Z. Bian, C. M. Vong, P. K. Wong, S. Wang, Fuzzy KNN method with adaptive nearest neighbors, IEEE Transactions on Cybernetics, 52 (2022), 5380-5393.

[4] H. L. Chen, C. C. Huang, X. G. Yu, X. Xu, X. Sun, G. Wang,  S. J. Wang, An efficient diagnosis system for detection of Parkinson's disease using fuzzy k-nearest neighbor approach, Expert Systems with Applications, 40 (2013), 263-271.

[5] A. J. P. Delima,  An enhanced K-nearest neighbor predictive model through metaheuristic optimization, International Journal of Engineering and Technology Innovation, 10 (2020), 280-292.

[6] Z. Deng, X. Zhu, D. Cheng, M. Zong,  S. Zhang, Efficient KNN classification algorithm for big data, Neurocomputing, 195 (2016), 143-148.

[7] N. Garc\'ia-Pedrajas, J. A. R. Del-Castillo,  G. Cerruela-Garcia,  A proposal for local K-values for k-nearest neighbor rule, IEEE Transactions on Neural Networks and Learning Systems, 28 (2015), 470-475.

[8] G. V. Gayathri, S. C. Satapathy, A survey on techniques for prediction of asthma, Smart Intelligent Computing and Applications, 159 (2020), 751-758.

[9] Z. Geler, V. Kurbalija, M. Ivanovic,  M. Radovanovic, Weighted KNN and constrained elastic distances for time-series classification, Expert Systems with Applications, 162 (2020). DOI:10.1016/j.eswa.2020.113829.

[10] J. Gou, L. Du, Y. Zhang,  T. Xiong, A new distance-weighted k-nearest neighbor classifier, Journal of Information and Computational Science, {\bf 9} (2012), 1429-1436.

[11] F. Harrou, A. Zeroual, Y. Sun, Traffic congestion monitoring using an improved KNN strategy, Measurement, 156 (2020). DOI:10.1016/j.measurement.2020.107534.

[12] V. Hashemi, Z Hasani, I. Sahraei, K. Borna, Hybrid algorithms of Whale optimization algorithm and k-nearest neighbor to predict the liver disease, EAI Endorsed Transaction on Context-Aware Systems and Applications, 6 (2019), 1-5.

[13] A. B. Hassanat, M. A. Abbadi, G. A. Altarawneh, A. A. Alhasanat, Solving the problem of the K parameter in the KNN classifier using an ensemble learning approach, International Journal of Computer Science and Information Security, 12 (2014), 33-39.

[14] J. Hu, H. Peng, J. Wang, W. Yu, KNN-P: A KNN classifier optimized by P systems, Theoretical Computer Science, 817 (2020), 55-65.

[15] M. A. Imron, B. Prasetyo, Improving algorithm accuracy k-nearest neighbor using z-score normalization and particle swarm optimization to predict customer churn, Journal of Soft Computing Exploration, 1 (2020), 56-62.

[16] B. B. Jia, M. L. Zhang, Multi-dimensional classification via KNN feature augmentation, Pattern Recognition, 106 (2020). DOI:10.1016/j.patcog.2020.107423.

[17] N. Jothi, N. A. Rashid, W. Husain, Data mining in healthcare-a review, Procedia Computer Science, 72 (2015), 306-313.

[18] I. Kavakiotis, O. Tsave, A. Salifoglou, N. Maglaveras, I. Vlahavas, I. Chouvarda, Machine learning and data mining methods in diabetes research, Computational and Structural Biotechnology Journal, 15 (2017), 104-116.

[19] P. Kumar, R. S. Thakur, Liver disorder detection using variable-neighbor weighted fuzzy K nearest neighbor approach, Multimedia Tools and Applications, 80 (2021), 16515-16535

[20] M. M. Kumbure, P. Luukka, M. Collan, A new fuzzy K-nearest neighbor classifier based on the Bonferroni mean, Pattern Recognition Letters, 140 (2020), 172-178.

[21] T. W. Liao, R. J. Kuo, Five discrete symbiotic organisms search algorithms for simultaneous optimization of feature subset and neighborhood size of KNN classification models, Applied Soft Computing, 64 (2018), 581-595.

[22] M. M. Mafarja, S. Mirjalili, Hybrid Whale optimization algorithm with simulated annealing for feature selection, Neurocomputing, 260 (2017), 302-312.

[23] N. Mastrogiannis, B. Boutsinas, I. Giannikos, A method for improving the accuracy of data mining classification algorithms, Computers and Operations Research, 36 (2009), 2829-2839.

[24] S. Mirjalili, A. Lewis, The Whale optimization algorithm, Advances in Engineering Software, 95 (2016), 51-67.

[25] T. M. Mohamed, Pulsar selection using fuzzy KNN classifier, Future Computing and Informatics Journal, 3 (2018), 1-6.

[26] R. Mukherji, A. Kundu, I. Mukherji, D. Gupta, P. Tiwari, A. Khanna, M. Shorfuzzaman, LOT-cloud based healthcare model for COVID-19 detection: An enhanced k-nearest neighbor classifier based approach, Computing, (2021),1-21. DOI:10.1007/s00607-021-00951-9.

[27] F. H. Rhee, C. Hwang, An interval type-2 fuzzy K-nearest neighbor, International Conference on Fuzzy Systems, Louis, MO, USA, (2003), 25-28.

[28] S. Sharma, K. M. Osei-Bryson, G. M. Kasper, Evaluation of an integrated knowledge discovery and data mining process model, Expert Systems with Applications, 39 (2012), 11335-11348.

[29] Y. Song, Y. Gu, R. Zhang, G. Yu, Bre-Partition: Optimized high-dimensional KNN search with Bregman distances, IEEE Transactions on Knowledge and Data Engineering, 34 (2020), 1053-1065.
[30] UCI Machine Learning Repository [Online], URL: https://archive.ics.uci.edu/ml/index.php.

[31] Z. Wang, J. Na, B. Zheng, An improved KNN classifier for epilepsy diagnosis, IEEE Access, 8 (2020), 100022-100030.

[32] Y. L. Yang, X. Y. Bai, A research on classification performance of fuzzy classifiers based on fuzzy set theory, Iranian Journal of Fuzzy Systems, 16 (2019), 15-27.

[33] H. Yigit, A weighting approach for KNN classifier, International Conference on Electronics, Computer and Computation, Ankara, Turkey, (2013), 228-231.

[34] S. Zeraatkar, F. Afsari, Interval-valued fuzzy and intuitionistic fuzzy-KNN for imbalanced data classification, Expert Systems with Applications, 184 (2021). DOI:10.1016/j.eswa.2021.115510.

[35] S. Zhang, Cost-sensitive KNN classification, Neurocomputing, 391 (2020), 234-242.

[36] S. Zhang, X. Li, M. Zong, X. Zhu, R. Wang, Efficient KNN classification with different numbers of nearest neighbors, IEEE Transactions on Neural Networks and Learning Systems, 29 (2018), 1774-1785.

[37] J. Zhang, Y. Niu, W. He, Using genetic algorithm to improve fuzzy KNN, International Conference on Computational Intelligence and Security, Suzhou, China, (2008), 475-479.

[38] C. Zhang, J. Yao, G. Hu, T. Schott, Applying feature-weighted gradient decent k-nearest neighbor to select promising projects for scientific funding, Computers, Materials and Continua, 64 (2020), 1741-1753.