Discrete-time signal processing
Discrete-time signal processing
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Representation and Recognition of Handwritten Digits Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
A Database for Handwritten Text Recognition Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fuzzy-Syntactic Approach to Allograph Modeling for Cursive Script Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Center CLICK: A Clustering Algorithm with Applications to Gene Expression Analysis
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
DHC: A Density-Based Hierarchical Clustering Method for Time Series Gene Expression Data
BIBE '03 Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering
Iterative Clustering of High Dimensional Text Data Augmented by Local Search
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Cluster Analysis for Gene Expression Data: A Survey
IEEE Transactions on Knowledge and Data Engineering
A Genetic Algorithm Using Hyper-Quadtrees for Low-Dimensional K-means Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analytically tractable case of fuzzy c-means clustering
Pattern Recognition
Clustering of unevenly sampled gene expression time-series data
Fuzzy Sets and Systems
Interactive exploration of fuzzy clusters using Neighborgrams
Fuzzy Sets and Systems
Handwritten word recognition with character and inter-character neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Validity-guided (re)clustering with applications to image segmentation
IEEE Transactions on Fuzzy Systems
Robust clustering methods: a unified view
IEEE Transactions on Fuzzy Systems
Hybrid fuzzy-neural systems in handwritten word recognition
IEEE Transactions on Fuzzy Systems
Generalized weighted conditional fuzzy clustering
IEEE Transactions on Fuzzy Systems
A possibilistic approach to clustering
IEEE Transactions on Fuzzy Systems
A new separation measure for improving the effectiveness of validity indices
Information Sciences: an International Journal
| Hi-index | 0.01 |
This paper presents a new partitioning algorithm, designated as the Adaptive C-Populations (ACP) clustering algorithm, capable of identifying natural subgroups and influential minor prototypes in an unlabeled dataset. In contrast to traditional Fuzzy C-Means clustering algorithms, which partition the whole dataset equally, adaptive clustering algorithms, such as that presented in this study, identify the natural subgroups in unlabeled datasets. In this paper, data points within a small, dense region located at a relatively large distance from any of the major cluster centers are considered to form a minor prototype. The aim of ACP is to adaptively separate these isolated minor clusters from the major clusters in the dataset. The study commences by introducing the mathematical model of the proposed ACP algorithm and demonstrates its convergence to a stable solution. The ability of ACP to detect minor prototypes is confirmed via its application to the clustering of three different datasets with different sizes and characteristics.