[1] I. D. Borlea, R. E. Precup, A. B. Borlea, D. Iercan, A unified form of fuzzy C-means and K-means algorithms and its partitional implementation, Knowledge-Based Systems, 214 (2021), 106731.
[2] R. A. Borzooei, B. Sheikh Hoseini, M. Mohseni Takallo, Results on t-fuzzy graphs, New Mathematics and Natural Computation, 16(01) (2020), 143-161.
[3] X. Boyen, L. Wehenkel, Fuzzy decision tree induction for power system security assessment, IFAC Proceedings Volumes, 28(26) (1995), 299-304.
[4] X. Boyen, L. Wehenkel, Automatic induction of fuzzy decision trees and its application to power system security assessment, Fuzzy Sets and Systems, 102 (1999), 3-19.
[5] W. Cao, X. Wang, Z. Ming, J. Gao, A review on neural networks with random weights, Neurocomputing, 275 (2018), 278-287.
[6] J. Demsar, Statistical comparisons of classifiers over multiple data sets, Journal of Machine Learning Research, 7 (2006), 1-30.
[7] D. Devi, S. K. Biswas, B. Purkayastha, Redundancy-driven modified Tomek-link based undersampling: A solution to class imbalance, Pattern Recognition Letters, 93 (2017), 3-12.
[8] J. A. Drakopoulos, Probabilities, possibilities, and fuzzy sets, Fuzzy Sets and Systems, 75 (2017), 1-15.
[9] D. Dua, K. Taniskidou, UCI machine learning repository, Irvine, CA: University of California, School of Information and Computer Science, (2017),
http://archive.ics.uci.edu/ml.
[10] M. Durairaj, J. H. M. Asha, Fuzzy probability based person recognition in smart environments, Journal of Fuzzy Systems, 40(5) (2021), 9437-9452.
[11] N. EI, I. Karabadji, I. Khelf, H. Seridi, et al., A data sampling and attribute selection strategy for improving decision tree construction, Expert Systems with Applications, 129 (2019), 84-96.
[12] X. Gu, F. L. Chung, S. Wang, Bayesian Takagi-Sugeno-Kang fuzzy classifier, IEEE Transactions on Fuzzy Systems, 25(9) (2017), 1655-1671.
[13] Q. Hu, X. Che, L. Zhang, et al., Rank entropy-based decision trees for monotonic classification, IEEE Transactions on Knowledge and Data Engineering, 24(11) (2012), 2052-2064.
[14] C. Jin, F. Li, Y. Li, A generalized fuzzy ID3 algorithm using generalized information entropy, Knowledge-Based Systems, 64 (2014), 13-21.
[15] A. Kumar, M. Hanmandlu, H. M. Gupta, Fuzzy binary decision tree for biometric based personal authentication, Neurocomputing, 99(1) (2013), 87-97.
[16] M. Lavioleue, J. W. Seaman, J. D. Barrett, W. H. Woodall, A probabilistic and statistical view of fuzzy methods, Technometrics, 37(3) (1995), 249-261.
[17] X. Liu, X. Feng, W. Pedrycz, Extraction of fuzzy rules from fuzzy decision trees: An axiomatic fuzzy sets (AFS) approach, Data and Knowledge Engineering, 84 (2013), 1-25.
[18] H. T. Nguyen, Fuzzy sets and probability, Fuzzy Sets and Systems, 90 (1997), 129-132.
[19] A. Paez, F. Lopez, M. Ruiz, Inducing non-orthogonal and non-linear decision boundaries in decision trees via interactive basis functions, Expert Systems with Applications, 122 (2019), 183-206.
[20] C. Pozna, R. E. Precup, Applications of signatures to expert systems modelling, Acta Polytechnica Hungarica, 11(2) (2014), 21-39.
[21] J. R. Quinlan, Induction of decision trees, Machine Learning, 1 (1986), 81-106.
[22] Y. Ren, X. Liu, J. Cao, A parsimony fuzzy rule-based classifier using axiomatic fuzzy set theory and support vector machines, Information Science, 181(23) (2011), 5180-5193.
[23] L. Rokach, O. Z. Maimon, Data mining with decision trees: Theory and applications, World Scientific, (2nd edition), 2015.
[24] S. K. Savas, E. Nasibov, A fuzzy ID3 induction for linguistic data sets, International Journal of Intelligent Systems, 33 (2018), 858-878.
[25] X. Wang, X. Liu, W. Pedrycz, L. Zhang, Fuzzy rule based decision trees, Pattern Recognition, 48 (2015), 50-59.
[26] J. Wang, P. Lu, H. Zhang, X. Chen, Method of multi-criteria group decision-making based on cloud aggregation operators with linguistic information, Information Sciences, 274 (2014), 177-191.
[27] J. Wang, Y. Qian, F. Li, Fusing fuzzy monotonic decision trees, IEEE Transactions on Fuzzy Systems, 28(5) (2020), 887-900.
[28] Y. Yang, X. Bai, A research on classification performance of fuzzy classifiers based on fuzzy set theory, Iranian Journal of Fuzzy Systems, 16 (2019), 15-27.
[29] W. Yi, M. Lu, Z. Liu, Multi-valued attribute and multi-labels data decision tree algorithm, International Journal of Machine Learning and Cybernetics, 2(2) (2011), 67-74.
[30] Y. Yuan, M. J. Shaw, Induction of fuzzy decision trees, Fuzzy Sets and Systems, 69 (1995), 125-139.
[31] L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353.
[32] J. Zhai, X. Z. Wang, S. Zhang, S. Hou, Tolerance rough fuzzy decision tree, Information Sciences, 465 (2018), 425-438.
[33] S. Zhao, H. Chen, C. Li, et al., A novel approach to building a robust fuzzy rough classifier, IEEE Transactions on Fuzzy Systems, 23(4) (2015), 769-786.
[34] H. Zhu, X. Wang, A cost-sensitive semi-supervised learning model based on uncertainty, Neurocomputing, 251 (2017), 106-114.