2.Hanchuan Peng, Fuhui Long, C. Ding. (2005). Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8), 1226–1238[10.1109/tpami.2005.159]
3.GuyonIsabelle, ElisseeffAndré. (2003). An introduction to variable and feature selection. Journal of Machine Learning Research[10.5555/944919.944968]
4.Usama M. Fayyad, Keki B. Irani. (1993). Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. International Joint Conference on Artificial Intelligence, 2, 1022–1027
5.R. Battiti. (1994). Using mutual information for selecting features in supervised neural net learning. IEEE Transactions on Neural Networks, 5(4), 537–550[10.1109/72.298224]
6.P.A. Estevez, M. Tesmer, C.A. Perez, J.M. Zurada. (2009). Normalized Mutual Information Feature Selection. IEEE Transactions on Neural Networks, 20(2), 189–201[10.1109/tnn.2008.2005601]
7.Jorge R. Vergara, Pablo A. Estévez. (2013). A review of feature selection methods based on mutual information. Neural Computing and Applications, 24(1), 175–186[10.1007/s00521-013-1368-0]
8.Gavin Brown, Adam Pocock, Mingjie Zhao, Mikel Luján. (2012). Conditional likelihood maximisation: a unifying framework for information theoretic feature selection. Research Explorer (The University of Manchester), 13(1), 27–66[link]
9.Huan Liu, R. Setiono. (2002). Chi2: feature selection and discretization of numeric attributes. , 388–391[10.1109/tai.1995.479783]
10.Mohamed Bennasar, Yulia Hicks, Rossitza Setchi. (2015). Feature selection using Joint Mutual Information Maximisation. Expert Systems with Applications, 42(22), 8520–8532[10.1016/j.eswa.2015.07.007]
11.David D. Lewis. (1992). Feature selection and feature extraction for text categorization. , 212[10.3115/1075527.1075574]
12.Salvador Garcia, J. Luengo, José Antonio Sáez, Victoria López, F. Herrera. (2012). A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning. IEEE Transactions on Knowledge and Data Engineering, 25(4), 734–750[10.1109/tkde.2012.35]
13.L.A. Kurgan, K.J. Cios. (2004). CAIM discretization algorithm. IEEE Transactions on Knowledge and Data Engineering, 16(2), 145–153[10.1109/tkde.2004.1269594]
14.Stefano Panzeri, Riccardo Senatore, Marcelo A. Montemurro, Rasmus S. Petersen. (2007). Correcting for the Sampling Bias Problem in Spike Train Information Measures. Journal of Neurophysiology, 98(3), 1064–1072[10.1152/jn.00559.2007]
15.S. Kullback, S. N. Roy. (1958). Some Aspects of Multivariate Analysis.. Journal of the American Statistical Association, 53(284), 1034[10.2307/2281973]
16.Stefano Panzeri, Alessandro Treves. (1996). Analytical estimates of limited sampling biases in different information measures. Network Computation in Neural Systems, 7(1), 87–107[10.1080/0954898x.1996.11978656]
17.R. Moddemeijer. (1989). On estimation of entropy and mutual information of continuous distributions. Signal Processing, 16(3), 233–248[10.1016/0165-1684(89)90132-1]
18.K.Z. Mao. (2004). Orthogonal Forward Selection and Backward Elimination Algorithms for Feature Subset Selection. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), 34(1), 629–634[10.1109/tsmcb.2002.804363]
19.Guo-Xun Yuan, Kai-Wei Chang, Cho‐Jui Hsieh, Chih‐Jen Lin. (2010). A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification. , 11(105), 3183–3234
20.Cheng-Jung Tsai, Chien-I. Lee, Wei-Pang Yang. (2007). A discretization algorithm based on Class-Attribute Contingency Coefficient. Information Sciences, 178(3), 714–731[10.1016/j.ins.2007.09.004]
21.Sina Tabakhi, Parham Moradi. (2015). Relevance–redundancy feature selection based on ant colony optimization. Pattern Recognition, 48(9), 2798–2811[10.1016/j.patcog.2015.03.020]
22.Jun Wang, Jin-Mao Wei, Zhenglu Yang, Shu-Qin Wang. (2017). Feature Selection by Maximizing Independent Classification Information. IEEE Transactions on Knowledge and Data Engineering, 29(4), 828–841[10.1109/tkde.2017.2650906]
23.La The Vinh, Sungyoung Lee, Young-Tack Park, Brian J. d’Auriol. (2011). A novel feature selection method based on normalized mutual information. Applied Intelligence, 37(1), 100–120[10.1007/s10489-011-0315-y]
24.Peter M. Rasmussen, Lars K. Hansen, Kristoffer H. Madsen, Nathan W. Churchill, Stephen C. Strother. (2011). Model sparsity and brain pattern interpretation of classification models in neuroimaging. Pattern Recognition, 45(6), 2085–2100[10.1016/j.patcog.2011.09.011]
25.Xuan Vinh Nguyen, Jeffrey Chan, Simone Romano, James Bailey. (2014). Effective global approaches for mutual information based feature selection. , 512–521[10.1145/2623330.2623611]
26.Jie Feng, Licheng Jiao, Fang Liu, Tao Sun, Xiangrong Zhang. (2015). Unsupervised feature selection based on maximum information and minimum redundancy for hyperspectral images. Pattern Recognition, 51, 295–309[10.1016/j.patcog.2015.08.018]
27.Nguyen Xuan Vinh, Shuo Zhou, Jeffrey Chan, James Bailey. (2015). Can high-order dependencies improve mutual information based feature selection?. Pattern Recognition, 53, 46–58[10.1016/j.patcog.2015.11.007]
28.Azlyna Senawi, Hua-Liang Wei, Stephen A. Billings. (2017). A new maximum relevance-minimum multicollinearity (MRmMC) method for feature selection and ranking. Pattern Recognition, 67, 47–61[10.1016/j.patcog.2017.01.026]
29.Fatemeh Barani, Mina Mirhosseini, Hossein Nezamabadi-pour. (2017). Application of binary quantum-inspired gravitational search algorithm in feature subset selection. Applied Intelligence, 47(2), 304–318[10.1007/s10489-017-0894-3]
30.YuanGuo-Xun, ChangKai-Wei, HsiehCho-Jui, LinChih-Jen. (2010). A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification. Journal of Machine Learning Research[10.5555/1756006.1953034]
31.B. Goebel, Z. Dawy, J. Hagenauer, J.C. Mueller. (2005). An approximation to the distribution of finite sample size mutual information estimates. , 1102–1106 Vol. 2[10.1109/icc.2005.1494518]
32.Gokhan Gulgezen, Zehra Cataltepe, Lei Yu. (2009). Stable and Accurate Feature Selection. Lecture notes in computer science, 455–468[10.1007/978-3-642-04180-8_47]
33.Kiran S Balagani, Vir V Phoha. (2010). On the Feature Selection Criterion Based on an Approximation of Multidimensional Mutual Information. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(7), 1342–1343[10.1109/tpami.2010.62]
34.Tofigh Naghibi, Sarah Hoffmann, Beat Pfister. (2014). A Semidefinite Programming Based Search Strategy for Feature Selection with Mutual Information Measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(8), 1529–1541[10.1109/tpami.2014.2372791]
35.W.-H. Au, K.C.C. Chan, A.K.C. Wong. (2006). A fuzzy approach to partitioning continuous attributes for classification. IEEE Transactions on Knowledge and Data Engineering, 18(5), 715–719[10.1109/tkde.2006.70]
36.Alberto Cano, Dat T. Nguyen, Sebastián Ventura, Krzysztof J. Cios. (2014). ur-CAIM: improved CAIM discretization for unbalanced and balanced data. Soft Computing, 20(1), 173–188[10.1007/s00500-014-1488-1]
37.Denoeux, Thierry, Masson, Marie-Hélène, SpringerLink (Online service). (2012). Belief Functions: Theory and Applications. Advances in intelligent and soft computing[10.1007/978-3-642-29461-7]
38.Ricardo de Matos Simoes, Frank Emmert-Streib. (2011). Influence of Statistical Estimators of Mutual Information and Data Heterogeneity on the Inference of Gene Regulatory Networks. PLoS ONE, 6(12), e29279[10.1371/journal.pone.0029279]
39.Sadia Sharmin, Amin Ahsan Ali, Muhammad Asif Hossain Khan, Mohammad Shoyaib. (2017). Feature Selection and Discretization based on Mutual Information. , 20, 1–6[10.1109/icivpr.2017.7890885]
40.N. L. Johnson, S. N. Roy. (1958). Some Aspects of Multivariate Analysis.. Journal of the Royal Statistical Society Series A (General), 121(4), 481[10.2307/2343316]
41.Hongrong Cheng, Zhiguang Qin, Weizhong Qian, Wei Liu. (2008). Conditional Mutual Information Based Feature Selection. , 103–107[10.1109/kam.2008.85]
42.Maria Fernanda Barbosa Wanderley, Vincent Gardeux, René Natowicz, Antônio P. Braga. (2013). GA-KDE-Bayes: An Evolutionary Wrapper Method Based on Non-Parametric Density Estimation Applied to Bioinformatics Problems. The European Symposium on Artificial Neural Networks, 155–160
43.Sadia Sharmin, Md Rifat Arefin, M. Abdullah-Al Wadud, Naushin Nower, Mohammad Shoyaib. (2015). SAL: An effective method for software defect prediction. , 184–189[10.1109/iccitechn.2015.7488065]
44.Jobaer Islam Khan, Alim Ul Gias, Md. Saeed Siddik, Md. Habibur Rahman, Shah Mostafa Khaled, Mohammad Shoyaib. (2014). An attribute selection process for software defect prediction. , 87, 1–4[10.1109/iciev.2014.6850791]
45.Mohammad Shoyaib, M. Abdullah-Al-Wadud, S. M. Zahid Ishraque, Oksam Chae. (2012). Facial Expression Classification Based on Dempster-Shafer Theory of Evidence. Advances in intelligent and soft computing, 213–220[10.1007/978-3-642-29461-7_25]
46.Junkai Ma, Haibo Luo, Wei Zhou, Yingchao Song, Bin Hui, Zheng Chang. (2017). Discriminative feature selection for visual tracking. Journal of Physics Conference Series, 844, 012046[10.1088/1742-6596/844/1/012046]
47.Kyugneun Lee, Ikjin Lee. (2017). Bayesian Network and Feature Selection for Rank Deficient Inverse Problem. World Academy of Science, Engineering and Technology, International Journal of Aerospace and Mechanical Engineering, 4(11)
48.J. R. Quinlan. (1992). C4.5: Programs for Machine Learning.
2.Xiwu Zhang, Lei Wang, Yan Su. (2020). Visual place recognition: A survey from deep learning perspective. Pattern Recognition, 113, 107760[10.1016/j.patcog.2020.107760]
3.Wenping Ma, Xiaobo Zhou, Hao Zhu, Longwei Li, Licheng Jiao. (2021). A two-stage hybrid ant colony optimization for high-dimensional feature selection. Pattern Recognition, 116, 107933[10.1016/j.patcog.2021.107933]
4.R. Vijayanand, D. Devaraj. (2020). A Novel Feature Selection Method Using Whale Optimization Algorithm and Genetic Operators for Intrusion Detection System in Wireless Mesh Network. IEEE Access, 8, 56847–56854[10.1109/access.2020.2978035]
5.Rasim Cekik, Alper Kursat Uysal. (2020). A novel filter feature selection method using rough set for short text data. Expert Systems with Applications, 160, 113691[10.1016/j.eswa.2020.113691]
7.Qinghua Zhang, Yunlong Cheng, Fan Zhao, Guoyin Wang, Shuyin Xia. (2021). Optimal Scale Combination Selection Integrating Three-Way Decision With Hasse Diagram. IEEE Transactions on Neural Networks and Learning Systems, 33(8), 3675–3689[10.1109/tnnls.2021.3054063]
8.Hui Huang, Rong Jia, Xiaoyu Shi, Jun Liang, Jian Dang. (2021). Feature selection and hyper parameters optimization for short-term wind power forecast. Applied Intelligence, 51(10), 6752–6770[10.1007/s10489-021-02191-y]
9.Josu Ircio, Aizea Lojo, Usue Mori, Jose A. Lozano. (2020). Mutual information based feature subset selection in multivariate time series classification. Pattern Recognition, 108, 107525[10.1016/j.patcog.2020.107525]
10.Kazi Mahmudul Hassan, Md. Rabiul Islam, Thanh Thi Nguyen, Md. Khademul Islam Molla. (2022). Epileptic seizure detection in EEG using mutual information-based best individual feature selection. Expert Systems with Applications, 193, 116414[10.1016/j.eswa.2021.116414]
11.Saúl Solorio-Fernández, J. Ariel Carrasco-Ochoa, José Francisco Martínez-Trinidad. (2021). A survey on feature selection methods for mixed data. Artificial Intelligence Review, 55(4), 2821–2846[10.1007/s10462-021-10072-6]
14.Shaobo Deng, Yulong Li, Junke Wang, Rutun Cao, Min Li. (2023). A feature-thresholds guided genetic algorithm based on a multi-objective feature scoring method for high-dimensional feature selection. Applied Soft Computing, 148, 110765[10.1016/j.asoc.2023.110765]
15.Zhenya Wang, Tao Liu, Xing Wu, Chang Liu. (2023). Application of an Oversampling Method Based on GMM and Boundary Optimization in Imbalance-Bearing Fault Diagnosis. IEEE Transactions on Industrial Informatics, 20(2), 1931–1940[10.1109/tii.2023.3282236]
16.Addisson Salazar, Luis Vergara, Enrique Vidal. (2022). A proxy learning curve for the Bayes classifier. Pattern Recognition, 136, 109240[10.1016/j.patcog.2022.109240]
17.Ping Zhang, Wanfu Gao. (2020). Feature selection considering Uncertainty Change Ratio of the class label. Applied Soft Computing, 95, 106537[10.1016/j.asoc.2020.106537]
18.Mehdi Joodaki, Mohammad Bagher Dowlatshahi, Nazanin Zahra Joodaki. (2021). An ensemble feature selection algorithm based on PageRank centrality and fuzzy logic. Knowledge-Based Systems, 233, 107538[10.1016/j.knosys.2021.107538]
19.Francisco Souza, Cristiano Premebida, Rui Araújo. (2022). High-order conditional mutual information maximization for dealing with high-order dependencies in feature selection. Pattern Recognition, 131, 108895[10.1016/j.patcog.2022.108895]
20.Zsolt János Viharos, Krisztián Balázs Kis, Ádám Fodor, Máté István Büki. (2021). Adaptive, Hybrid Feature Selection (AHFS). Pattern Recognition, 116, 107932[10.1016/j.patcog.2021.107932]
21.G. S. Thejas, Sajal Raj Joshi, S. S. Iyengar, N. R. Sunitha, Prajwal Badrinath. (2019). Mini-Batch Normalized Mutual Information: A Hybrid Feature Selection Method. IEEE Access, 7, 116875–116885[10.1109/access.2019.2936346]
22.Li Zhang, Xiaobo Chen. (2021). Feature Selection Methods Based on Symmetric Uncertainty Coefficients and Independent Classification Information. IEEE Access, 9, 13845–13856[10.1109/access.2021.3049815]
23.Md. Eusha Kadir, Pritom Saha Akash, Sadia Sharmin, Amin Ahsan Ali, Mohammad Shoyaib. (2019). Can a simple approach identify complex nurse care activity?. , 736–740[10.1145/3341162.3344859]
24.Jiucheng Xu, Kanglin Qu, Yuanhao Sun, Jie Yang. (2022). Feature selection using self-information uncertainty measures in neighborhood information systems. Applied Intelligence, 53(4), 4524–4540[10.1007/s10489-022-03760-5]
25.Yang Zhang, Caibo Deng, Ran Zhao, Sebastian leto. (2020). RETRACTED: A novel integrated price and load forecasting method in smart grid environment based on multi-level structure. Engineering Applications of Artificial Intelligence, 95, 103852[10.1016/j.engappai.2020.103852]
26.Md. Nazmul Haque, M. Tanjid Hasan Tonmoy, Saif Mahmud, Amin Ahsan Ali, Muhammad Asif Hossain Khan, Mohammad Shoyaib. (2019). GRU-based Attention Mechanism for Human Activity Recognition. 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), 1–6[10.1109/icasert.2019.8934659]
27.Md. Nazmul Haque, Mahir Mahbub, Md. Hasan Tarek, Lutfun Nahar Lota, Amin Ahsan Ali. (2019). Nurse care activity recognition. , 719–723[10.1145/3341162.3344848]
28.Amina Benkessirat, Nadjia Benblidia. (2019). Fundamentals of Feature Selection: An Overview and Comparison. , 1–6[10.1109/aiccsa47632.2019.9035281]
29.Kanglin Qu, Jiucheng Xu, Ziqin Han, Shihui Xu. (2023). Maximum relevance minimum redundancy-based feature selection using rough mutual information in adaptive neighborhood rough sets. Applied Intelligence, 53(14), 17727–17746[10.1007/s10489-022-04398-z]
30.Yeming Dai, Xinyu Yang, Mingming Leng. (2022). Forecasting power load: A hybrid forecasting method with intelligent data processing and optimized artificial intelligence. Technological Forecasting and Social Change, 182, 121858[10.1016/j.techfore.2022.121858]
31.Rihab Said, Maha Elarbi, Slim Bechikh, Carlos Artemio Coello Coello, Lamjed Ben Said. (2022). Discretization-Based Feature Selection as a Bilevel Optimization Problem. IEEE Transactions on Evolutionary Computation, 27(4), 893–907[10.1109/tevc.2022.3192113]
32.Shihe Wang, Jianfeng Ren, Ruibin Bai. (2023). A semi-supervised adaptive discriminative discretization method improving discrimination power of regularized naive Bayes. Expert Systems with Applications, 225, 120094[10.1016/j.eswa.2023.120094]
33.Zhang, Sikai, Lang, Zi-Qiang. (2021). Orthogonal Least Squares Based Fast Feature Selection for Linear Classification. arXiv (Cornell University)[10.1016/j.patcog.2021.108419]
34.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]
35.Madhuri Gupta, Bharat Gupta. (2020). A novel gene expression test method of minimizing breast cancer risk in reduced cost and time by improving SVM-RFE gene selection method combined with LASSO. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics, 18(2), 139–153[10.1515/jib-2019-0110]
36.Gaoteng Yuan, Lu Lu, Xiaofeng Zhou. (2023). Feature selection using a sinusoidal sequence combined with mutual information. Engineering Applications of Artificial Intelligence, 126, 107168[10.1016/j.engappai.2023.107168]
37.Haiyang Pan, Yu Yang, Jinde Zheng, Xin Li, Junsheng Cheng. (2020). Symplectic interactive support matrix machine and its application in roller bearing condition monitoring. Neurocomputing, 398, 1–10[10.1016/j.neucom.2020.01.074]
38.Zana Azeez Kakarash, Farhad Mardukhia, Parham Moradi. (2022). Multi-label feature selection using density-based graph clustering and ant colony optimization. Journal of Computational Design and Engineering, 10(1), 122–138[10.1093/jcde/qwac120]
39.Shihe Wang, Jianfeng Ren, Ruibin Bai, Yuan Yao, Xudong Jiang. (2023). A Max-Relevance-Min-Divergence criterion for data discretization with applications on naive Bayes. Pattern Recognition, 149, 110236[10.1016/j.patcog.2023.110236]
40.Honglin Xiong, Chongjun Fan, Hongmin Chen, Yun Yang, Collins Opoku ANTWI, Xiaomao Fan. (2022). A Novel Approach to Air Passenger Index Prediction: Based on Mutual Information Principle and Support Vector Regression Blended Model. SAGE Open, 12(1)[10.1177/21582440211071102]
41.Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour. (2025). Building electrical consumption patterns forecasting based on a novel hybrid deep learning model. Results in Engineering, 26, 104522[10.1016/j.rineng.2025.104522]
42.Ermin Zhao, Zhennan Zhang, Navid Bohlooli. (2020). RETRACTED: Cost and load forecasting by an integrated algorithm in intelligent electricity supply network. Sustainable Cities and Society, 60, 102243[10.1016/j.scs.2020.102243]
43.Gaoteng Yuan, Yi Zhai, Jiansong Tang, Xiaofeng Zhou. (2023). CSCIM_FS: Cosine similarity coefficient and information measurement criterion-based feature selection method for high-dimensional data. Neurocomputing, 552, 126564[10.1016/j.neucom.2023.126564]
44.Hyunki Lim. (2023). Low-rank learning for feature selection in multi-label classification. Pattern Recognition Letters, 172, 106–112[10.1016/j.patrec.2023.05.036]
45.Salvatore Carta, Anselmo Ferreira, Diego Reforgiato Recupero, Roberto Saia. (2021). Credit scoring by leveraging an ensemble stochastic criterion in a transformed feature space. Progress in Artificial Intelligence, 10(4), 417–432[10.1007/s13748-021-00246-2]
46.Li Zhang. (2021). A Feature Selection Algorithm Integrating Maximum Classification Information and Minimum Interaction Feature Dependency Information. Computational Intelligence and Neuroscience, 2021(1), 3569632[10.1155/2021/3569632]
47.Zhiwei Li, Yibin Wang, Jili Zhang, Hua Guan. (2023). Feature selection for indoor temperature prediction in large-space buildings based on transfer entropy and life cycle cost. Building and Environment, 243, 110722[10.1016/j.buildenv.2023.110722]
48.Jianlin Wang, Xuebing Dai, Huimin Luo, Chaokun Yan, Ge Zhang, Junwei Luo. (2021). MI_DenseNetCAM: A Novel Pan-Cancer Classification and Prediction Method Based on Mutual Information and Deep Learning Model. Frontiers in Genetics, 12, 670232[10.3389/fgene.2021.670232]
49.G. Manikandan, S. Abirami. (2021). Feature Selection and Machine Learning Models for High‐Dimensional Data: State‐of‐the‐Art. , 43–63[10.1002/9781119818717.ch3]
50.Chaoqun Hu, Yonghua Li, Zhe Chen, Zhihui Men. (2023). A novel rolling bearing fault diagnosis method based on parameter optimization variational mode decomposition with feature weighted reconstruction and multi-target attention convolutional neural networks under small samples. Review of Scientific Instruments, 94(7)[10.1063/5.0158412]
51.Gaoteng Yuan, Xiang Li, Ping Qiu, Xiaofeng Zhou. (2024). Feature selection method based on wavelet similarity combined with maximum information coefficient. Information Sciences, 699, 121801[10.1016/j.ins.2024.121801]
52.Fernando Jimenez, Gracia Sanchez, Jose Palma, Luis Miralles-Pechuan, Juan A. Botia. (2022). Multivariate Feature Ranking With High-Dimensional Data for Classification Tasks. IEEE Access, 10, 60421–60437[10.1109/access.2022.3180773]
53.Morteza Zadkarami, Ali Akbar Safavi, Krist V. Gernaey, Pedram Ramin. (2024). A Process Monitoring Framework for Imbalanced Big Data: A Wastewater Treatment Plant Case Study. IEEE Access, 12, 132139–132158[10.1109/access.2024.3454516]
54.Mohammed Sayeeduddin Habeeb, Tummala Ranga Babu. (2024). Coarse and fine feature selection for Network Intrusion Detection Systems (<scp>IDS</scp>) in <scp>IoT</scp> networks. Transactions on Emerging Telecommunications Technologies, 35(4)[10.1002/ett.4961]
55.Puloma Roy, Sadia Sharmin, Amin Ahsan Ali, Mohammad Shoyaib. (2020). Discretization and Feature Selection Based on Bias Corrected Mutual Information Considering High-Order Dependencies. Lecture notes in computer science, 830–842[10.1007/978-3-030-47426-3_64]
56.Chia-Hao Tu, Chunshien Li. (2020). Multitarget prediction using an aim-object-based asymmetric neuro-fuzzy system: A novel approach. Neurocomputing, 389, 155–169[10.1016/j.neucom.2019.12.113]
57.Lang Zhao, Yiqun Zhang, Xiaopeng Luo, Yue Zhang, Yiu-Ming Cheung, Kangshun Li. (2023). Selecting Heterogeneous Features Based on Unified Density-Guided Neighborhood Relation for Complex Biomedical Data Analysis. , 771–778[10.1109/bibm58861.2023.10386030]
58.Xin-zhi Li, Xian-pu Xiao, Kang Xie, Hong-fei Yang, Liang Xu, Tai-feng Li. (2024). A generalizable parameter calibration framework for discrete element method and application in the compaction of red-bed soft rocks. Construction and Building Materials, 444, 137734[10.1016/j.conbuildmat.2024.137734]
59.Chaoqun Hu, Yonghua Li, Zhe Chen, Denglong Wang, Zhihui Men. (2023). Research on fault diagnosis of rolling bearing based on multi-sensor bi-layer information fusion under small samples. Review of Scientific Instruments, 94(11)[10.1063/5.0174359]
60.José Patiño, Ángel Encalada-Dávila, José Sampietro, Christian Tutivén, Carlos Saldarriaga, Imin Kao. (2023). Damping Ratio Prediction for Redundant Cartesian Impedance-Controlled Robots Using Machine Learning Techniques. Mathematics, 11(4), 1021[10.3390/math11041021]
61.Rasim Cekik, Alper Kursat Uysal. (2022). A new metric for feature selection on short text datasets. Concurrency and Computation Practice and Experience, 34(13)[10.1002/cpe.6909]
62.Matin Chiregi, Mahdi Mazinani, Mitra Mirzarezaee. (2025). A new feature selection method using deep learning and graph representation in high-dimensional datasets. Knowledge-Based Systems, 329, 114338[10.1016/j.knosys.2025.114338]
63.Usharani Bhimavarapu, M. Sreedevi. (2022). Kurtosis-Based Feature Selection Method using Symmetric Uncertainty to Predict the Air Quality Index. Computer Science Journal of Moldova, 30(3(90)), 360–375[10.56415/csjm.v30.19]
64.Karpagalingam Thirumoorthy, Jerold John Britto. (2024). A two-stage feature selection approach using hybrid elitist self-adaptive cat and mouse based optimization algorithm for document classification. Expert Systems with Applications, 254, 124396[10.1016/j.eswa.2024.124396]
65.Bo Zhang, Wei Teng, Honghua Bai, Weiling Huang, Dikang Peng, Yibing Liu. (2024). Sparsity and Periodicity-Induced Symplectic Geometry Decomposition for Incipient Fault Diagnosis of Wind Turbine Gearbox. IEEE Transactions on Instrumentation and Measurement, 73, 1–12[10.1109/tim.2024.3472828]
66.Amjad Ali, Faiz Jillani, Rabbiah Zaheer, Ahmad Karim, Yasser Obaid Alharbi, Mohammad Alsaffar, Khalid Alhamazani. (2022). Practically Implementation of Information Loss: Sensitivity, Risk by Different Feature Selection Techniques. IEEE Access, 10, 27643–27654[10.1109/access.2022.3152963]
67.Xuemin Tan, Chao Guo, Tao Jiang, Kechang Fu, Nan Zhou, Jianying Yuan, Guoliang Zhang. (2021). A new semi-supervised algorithm combined with MCICA optimizing SVM for motion imagination EEG classification. Intelligent Data Analysis, 25(4), 863–877[10.3233/ida-205188]
68.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]
69.Jiucheng Xu, Miaoxian Ma, Shan Zhang, Wulin Niu. (2025). Feature selection based on multi-perspective dynamic neighbourhood entropy measures in a dynamic neighbourhood rough set. Applied Intelligence, 55(6)[10.1007/s10489-025-06336-1]
71.Minggang Dong, Ming Liu, Chao Jing. (2022). One-against-all-based Hellinger distance decision tree for multiclass imbalanced learning. Frontiers of Information Technology & Electronic Engineering, 23(2), 278–290[10.1631/fitee.2000417]
72.Sang-Hong Lee. (2021). Classification of epileptic seizure using feature selection based on fuzzy membership from EEG signal. Technology and Health Care, 29(S1), 519–529[10.3233/thc-218049]
73.Shanmin Yang, Xiao Yang, Yi Lin, Peng Cheng, Yi Zhang, Jianwei Zhang. (2021). Heterogeneous Face Recognition with Attention-guided Feature Disentangling. , 4137–4145[10.1145/3474085.3475546]
74.Md. Mumtahin Habib Ullah Mazumder, Md. Eusha Kadir, Sadia Sharmin, Md. Shariful Islam, Muhammad Mahbub Alam. (2023). cFEM: a cluster based feature extraction method for network intrusion detection. International Journal of Information Security, 22(5), 1355–1369[10.1007/s10207-023-00694-y]
75.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]
76.Yan Zhao, Qian Liu, Zhe Zhang, Zenghao Bi, Yanhong Bai, Ying Zhou, Hongyan Liu, Gaobin Pu, Yu Zhang, Yu Zhang, Jia Li, Yongqing Zhang, Yongqing Zhang. (2020). Estimating the Q-marker concentrations of Salvia miltiorrhiza via a long short-term memory algorithm using climatic factors and metabolic profiling. Industrial Crops and Products, 156, 112883[10.1016/j.indcrop.2020.112883]
77.Rahweni Ocviani, Mustakim, Rusliyawati, Muhammad Muharrom, Imam Ahmad, Sepriano. (2023). Classification of Student Graduation Using Backpropagation Neural Network with Features Selection and Dimensions Reduction. , 1–5[10.1109/icoris60118.2023.10352284]
78.Rasim ÇEKİK, Mahmut KAYA. (2023). A New Feature Selection Metric Based on Rough Sets and Information Gain in Text Classification. Gazi University Journal of Science Part A Engineering and Innovation, 10(4), 472–486[10.54287/gujsa.1379024]
79.Wei Zhang, Yongxiang Liu, Zhuo Wang, Jianyong Wang. (2023). Learning to Binarize Continuous Features for Neuro-Rule Networks. , 4584–4592[10.24963/ijcai.2023/510]
80.Amir Hossein Hamedi, Hossein Abolghasemi, Saeid Shokri, Hadi Jafar Nia, Farshad Moayedi. (2023). Integrating Artificial Immune Genetic Algorithm and Metaheuristic Ant Colony Optimizer with Two-Dose Vaccination and Modeling for Residual Fluid Catalytic Cracking Process. Arabian Journal for Science and Engineering, 48(12), 16329–16341[10.1007/s13369-023-07882-x]
81.Hanmo You, Zan Wang, Xuyang Chen, Junjie Chen, Jun Sun, Shuang Liu, Zishuo Dong. (2025). Mitigating Regression Faults Induced by Feature Evolution in Deep Learning Systems. ACM Transactions on Software Engineering and Methodology, 34(6), 1–33[10.1145/3712199]
82.Martin J.-D. Otis, Julien Vandewynckel. (2021). A Many-Objective Simultaneous Feature Selection and Discretization for LCS-Based Gesture Recognition. Applied Sciences, 11(21), 9787[10.3390/app11219787]
83.Mina Rafla, Nicolas Voisine, Bruno Crémilleux, Marc Boullé. (2023). A Non-parametric Bayesian Approach for Uplift Discretization and Feature Selection. Lecture notes in computer science, 239–254[10.1007/978-3-031-26419-1_15]
85.Yiqun Zhang, Xinxi Chen, Lang Zhao, Yuzhu Ji, Peng Liu, Yiu-Ming Cheung. (2025). Online Heterogeneous Feature Selection. IEEE Transactions on Cybernetics, 56(4), 2224–2237[10.1109/tcyb.2025.3635888]
86.Chandra Sekhar Vorugunti, Viswanath Pulabaigari, Prerana Mukherjee, Rama Krishna Sai Subrahmanyam Gorthi. (2024). Inf-Att-OSVNet: information theory based feature selection and deep attention networks for online signature verification. Multimedia Tools and Applications, 84(19), 21373–21415[10.1007/s11042-024-19886-2]
87.Suravi Akhter, Sumon Ahmed, Ahmedul Kabir, Mohammad Shoyaib. (2022). A Relief Based Feature Subset Selection Method. Dhaka University Journal of Applied Science and Engineering, 6(2), 7–13[10.3329/dujase.v6i2.59214]
88.Guan-Yu Huang, Chiao-Yun Hung, Bo-Wei Chen. (2022). Image feature selection based on orthogonal <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:msub><mml:mi>ℓ</mml:mi><mml:mrow><mml:mtext>2</mml:mtext><mml:mo>,</mml:mo><mml:mn>0</mml:mn></mml:mrow></mml:msub></mml:math> norms. Measurement, 199, 111310[10.1016/j.measurement.2022.111310]
89.Yuan Sun, Wei Wang, Michael Kirley, Xiaodong Li, Jeffrey Chan. (2020). Revisiting Probability Distribution Assumptions for Information Theoretic Feature Selection. Proceedings of the AAAI Conference on Artificial Intelligence, 34(04), 5908–5915[10.1609/aaai.v34i04.6050]
90.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]
91.Md. Hasan Tarek, Md. Eusha Kadir, Mahir Mahbub, Pritom Saha Akash, Amin Ahsan Ali, Mohammad Shoyaib. (2020). Mutual Information based Feature Selection for Nurse Care Activity Recognition. , 1–6[10.1109/icievicivpr48672.2020.9306645]
92.JUNJIANG ZHU, YU PU, HAO HUANG, YUXUAN WANG, XIAOLU LI, TIANHONG YAN. (2021). A FEATURE SELECTION-BASED ALGORITHM FOR DETECTION OF ATRIAL FIBRILLATION USING SHORT-TERM ECG. Journal of Mechanics in Medicine and Biology, 21(05), 2140013[10.1142/s0219519421400133]
93.Rayene Bounab, Bouchra Guelib, Sarra Benzerogue, Karim Zarour. (2024). Optimizing Machine Learning for Healthcare Fraud Detection: A Framework Using Hybrid Feature Selection and Hyperparameter Tuning. , 1–8[10.1109/icaase64542.2024.10851054]
94.Kamal Deep, Manoj Thakur. (2025). Multiobjective evolutionary algorithm based wrapper approach for hyperspectral band selection. Engineering Applications of Artificial Intelligence, 159, 111631[10.1016/j.engappai.2025.111631]
95.Kamal Deep, Bhisham Dev Verma, Manoj Thakur. (2025). An ant interaction scheme based wrapper strategy for hyperspectral band selection. Infrared Physics & Technology, 145, 105726[10.1016/j.infrared.2025.105726]
96.Mohammad Hatami, Parham Moradi, Sadegh Sulaimany, Mahdi Jalili. (2025). Maximum relevant minimum redundant multi-label feature selection using ant colony optimization. Engineering Applications of Artificial Intelligence, 161, 112007[10.1016/j.engappai.2025.112007]
97.Tianyu Cheng, Jin Xiao. (2025). Cost-constrained feature selection using gradient boosting decision tree. Engineering Applications of Artificial Intelligence, 162, 112751[10.1016/j.engappai.2025.112751]
98.Shihe Wang, Jianfeng Ren, Ruibin Bai. (2022). A Semi-Supervised Adaptive Discriminative Discretization Method Improving Discrimination Power of Regularized Naive Bayes. SSRN Electronic Journal[10.2139/ssrn.4281601]
99.Jiacheng Tu, Haiyan Yu, Ruxin Ding, Shihe Wang, Jianfeng Ren, Xudong Jiang. (2025). Jointly Optimizing Data Discretization and Naive Bayes Classifier via Multi-Objective Optimization. , 1–5[10.1109/icassp49660.2025.10890736]
100.K. H. Tie, A. Senawi, Z. L. Chuan. (2022). An Observation of Different Clustering Algorithms and Clustering Evaluation Criteria for a Feature Selection Based on Linear Discriminant Analysis. Lecture notes in electrical engineering, 497–505[10.1007/978-981-19-2095-0_42]
101.Md. Hasan Tarek, Md. Eusha Kadir, Sadia Sharmin, Abu Ashfaqur Sajib, Amin Ahsan Ali, Mohammad Shoyaib. (2021). Feature Subset Selection based on Redundancy Maximized Clusters. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 521–526[10.1109/icmla52953.2021.00087]
102.Yeming Dai, Xinyu Yang. (2021). Forecasting Power Load: A Hybrid Forecasting Method with Intelligent Data Processing and Optimized Artificial Intelligence. SSRN Electronic Journal[10.2139/ssrn.3986242]
103.Farhatul Janan, Naimur Rahman Chowdhury, Kais Zaman. (2022). A New Approach for Control Chart Pattern Recognition Using Nonlinear Correlation Measure. SN Computer Science, 3(5)[10.1007/s42979-022-01243-5]
105.L. Meenachi, S. Ramakrishnan. (2024). Review on hybrid feature selection and classification of microarray gene expression data. Elsevier eBooks, 319–340[10.1016/b978-0-44-313233-9.00020-5]
106.Honglin Xiong, Chongjun Fan, Collins Opoku ANTWI, yun yang, Xiaomao fan. (2020). An Integrated Approach to Air Passenger Index Prediction: Mutual Information Principle and Support Vector Regression (MI-Svr) Blended Model. Preprints.org[10.20944/preprints202008.0448.v1]
107.Honglin Xiong, Chongjun Fan, Collins Opoku Antwi, Yun Yang, Xiaomao Fan. (2020). An Integrated Approach to Air Passenger Index Prediction: Mutual Information Principle and Support Vector Regression (MI-SVR) Blended Model. Preprints.org[10.20944/preprints202008.0392.v1]
108.Tingjian Chen, Haoliang Yuan, Ming Yin. (2022). Hierarchical unsupervised multi-view feature selection. International Journal of Wavelets Multiresolution and Information Processing, 20(06)[10.1142/s0219691322500242]
109.Wei Zhou, Wenqiang Zhu, Jin Chen, Zeshui Xu. (2025). The cross-interval reconstruction and heuristic calculation to deal with the continuous-valued attribute in the learning process. Applied Soft Computing, 172, 112897[10.1016/j.asoc.2025.112897]
110.Zhong Li, Yang Jing, Lijing Yao, Binbin Gan. (2019). Unsupervised Feature Selection Algorithm Based on Information Gain. [10.2991/acsr.k.191223.015]
111.Zewen Zhang, Sheng Zhou, Chunzheng Cao. (2024). Curve Classification Based on Mean-Variance Feature Weighting and Its Application. Computers, materials & continua/Computers, materials & continua (Print), 79(2), 2465–2480[10.32604/cmc.2024.049605]
112.Wang, Shihe, Ren, Jianfeng, Bai, Ruibin. (2021). A Semi-Supervised Adaptive Discriminative Discretization Method Improving Discrimination Power of Regularized Naive Bayes. arXiv (Cornell University)[10.48550/arxiv.2111.10983]
113.Suravi Akhter, Muhammad Mahbub Alam, Md. Shariful Islam, M. Arshad Momen, Md. Shariful Islam, Mohammad Shoyaib. (2024). Low-cost orthogonal basis-core extraction for classification and reconstruction using tensor ring. Pattern Recognition, 154, 110548[10.1016/j.patcog.2024.110548]
114.Dan Liu Dan Liu, Shu-Wen Yao Dan Liu, Hai-Long Zhao Shu-Wen Yao, Xin Sui Hai-Long Zhao, Yong-Qi Guo Xin Sui, Mei-Ling Zheng Yong-Qi Guo, Li Li Mei-Ling Zheng. (2022). Research on Mutual Information Feature Selection Algorithm Based on Genetic Algorithm. 電腦學刊, 33(6), 131–141[10.53106/199115992022123306011]
115.Bo Yang, Shun Zhang, Zhixing Deng, Na Su, Shaopeng Chen, Di Zhu. (2025). Macro–Mesoscopic Analysis and Parameter Calibration of Rock–Soil Strength Degradation Under Different Water Contents. Applied Sciences, 15(18), 10254[10.3390/app151810254]
116.Yi-Cheng Shih, Tian-Shyr Dai, Yen-Wu Ti, Yun Kuo, Wun-Hao Wang, Ying-Ping Chen. (2025). A Novel Feature Filtering Mechanism to Avoid Concept Shifts from Deteriorating Model Predictability. , 236–243[10.1109/bigcomp64353.2025.00053]
117.Rajkumar N, J. Preetha Roselyn. (2025). Golden eagle optimization approach for feature selection and XGBoost algorithm-based intrusion detection system in wireless mesh networks of smart grid. Journal of the Chinese Institute of Engineers, 48(8), 1312–1319[10.1080/02533839.2025.2517355]
118.Sikai Zhang, Zi-Qiang Lang. (2021). Orthogonal least squares based fast feature selection for linear classification. Pattern Recognition, 123, 108419[10.1016/j.patcog.2021.108419]
119.Md Hasan Tarek, Suravi Akhter, Sumon Ahmed, Md Shariful Islam, Mohammad Shoyaib, Zerina Begum. (2023). A Clustering based Feature Selection Approach using Maximum Spanning Tree. Dhaka University Journal of Applied Science and Engineering, 7(2), 47–55[10.3329/dujase.v7i2.65094]
120.Nishat Tasnim Mim, Md. Eusha Kadir, Suravi Akhter, Muhammad Asif Hossain Khan. (2024). An overlapping conscious relief-based feature subset selection method. International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering, 14(2), 2068[10.11591/ijece.v14i2.pp2068-2075]
121.Hasnain Hossain, Tahmid Bin Mahmud, A K M Mahbubur Rahman, M Ashraful Amin, Amin Ahsan Ali. (2021). Comparing recent Swarm Algorithms with Information Theoretic Filter criterion for Feature Selection. 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), 1–6[10.1109/icecet52533.2021.9698430]
122.Agghey, Abel. (2022). Detection and prevention of username enumeration attack on SSH protocol: machine learning approach. [10.58694/20.500.12479/1628]
123.Janani Kesavan, Kavitha Seethapathy, Satheeshkumar J, Rakkiyappan Rajan, Amudha Thangavel. (2022). Multi-Criteria Decision Making Methods for Ensemble Feature Selection using q-Rung Orthopair Hesitant Fuzzy Distance and Similarity Measures. Research Square[10.21203/rs.3.rs-1583632/v1]
124.Iman Ghodratitoostani. (2022). Plataforma de computação neurocognitiva:protótipo na reabilitação do zumbido através da regulação da emoção concomitante com a estimulação transcraniana por corrente diret. [10.11606/t.55.2022.tde-03032023-100207]
125.Zheli An, Yangsheng Ye, Taifeng Li, Huiying Yang, Xianpu Xiao, Kang Xie, Ronghui Yan. (2026). Multiscale DEM-FDM framework for subgrade dynamic response under high-speed railway speed-up. Transportation Geotechnics, 61, 102060[10.1016/j.trgeo.2026.102060]
126.Francesco De Santis, Danilo Giordano, Marco Mellia. (2025). GLEm-Net: Unified framework for data reduction with categorical and numerical features. Knowledge-Based Systems, 334, 115049[10.1016/j.knosys.2025.115049]
128.Md Nazmul Haque, Sadia Sharmin, Amin Ahsan Ali, Abu Ashfaqur Sajib, Mohammad Shoyaib. (2020). Use of relevancy and complementary information for discriminatory gene selection from high-dimensional cancer data. bioRxiv (Cold Spring Harbor Laboratory)[10.1101/2020.02.25.964304]