L1-norm based fuzzy clustering
Fuzzy Sets and Systems
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Nonlinear component analysis as a kernel eigenvalue problem
Neural Computation
ACM Computing Surveys (CSUR)
Fuzzy Set Theoretic Adjustment to Training Set Class Labels Using Robust Location Measures
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3 - Volume 3
Towards a robust fuzzy clustering
Fuzzy Sets and Systems - Data analysis
Clustering Incomplete Data Using Kernel-Based Fuzzy C-means Algorithm
Neural Processing Letters
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Training of support vector machines with Mahalanobis kernels
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
A novel kernelized fuzzy C-means algorithm with application in medical image segmentation
Artificial Intelligence in Medicine
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
Generalized fuzzy c-means clustering strategies using Lp norm distances
IEEE Transactions on Fuzzy Systems
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
Mercer kernel-based clustering in feature space
IEEE Transactions on Neural Networks
Multiple network fusion using fuzzy logic
IEEE Transactions on Neural Networks
Constructing accurate fuzzy classifiers: A new adaptive method for rule-weight specification
International Journal of Knowledge-based and Intelligent Engineering Systems
A simultaneous learning framework for clustering and classification
Pattern Recognition
A multiobjective simultaneous learning framework for clustering and classification
IEEE Transactions on Neural Networks
Voting based extreme learning machine
Information Sciences: an International Journal
Simultaneous clustering and classification over cluster structure representation
Pattern Recognition
Fuzzy classifier based on fuzzy support vector machine
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Fuzzy relational classifier (FRC) is a recently proposed two-step nonlinear classifier. At first, the unsupervised fuzzy c-means (FCM) clustering is performed to explore the underlying groups of the given dataset. Then, a fuzzy relation matrix indicating the relationship between the formed groups and the given classes is constructed for subsequent classification. It has been shown that FRC has two advantages: interpretable classification results and avoidance of overtraining. However, FRC not only lacks the robustness which is very important for a classifier, but also fails on the dataset with non-spherical distributions. Moreover, the classification mechanism of FRC is sensitive to the improper class labels of the training samples, thus leading to considerable decline in classification performance. The purpose of this paper is to develop a Robust FRC (RFRC) algorithm aiming at overcoming or mitigating all of the above disadvantages of FRC and maintaining its original advantages. In the proposed RFRC algorithm, we employ our previously proposed robust kernelized FCM (KFCM) to replace FCM to enhance its robustness against outliers and its suitability for the non-spherical data structures. In addition, we incorporate the soft class labels into the classification mechanism to improve its performance, especially for the datasets containing the improper class labels. The experimental results on 2 artificial and 11 real-life benchmark datasets demonstrate that RFRC algorithm can consistently outperform FRC in classification performance.