Algorithms for clustering data
Algorithms for clustering data
Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Agglomerative clustering of symbolic objects using the concepts of both similarity and dissimilarity
Pattern Recognition Letters
A conceptual version of the K-means algorithm
Pattern Recognition Letters
A monothetic clustering method
Pattern Recognition Letters
ACM Computing Surveys (CSUR)
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data
Self-Organizing Maps
Neural Computation and Self-Organizing Maps; An Introduction
Neural Computation and Self-Organizing Maps; An Introduction
Generalized relevance learning vector quantization
Neural Networks - New developments in self-organizing maps
Clustering of interval data based on city-block distances
Pattern Recognition Letters
Fuzzy Neural Network Theory and Application
Fuzzy Neural Network Theory and Application
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing (The Handbooks of Fuzzy Sets)
Adaptive Hausdorff distances and dynamic clustering of symbolic interval data
Pattern Recognition Letters
Dynamic clustering for interval data based on L2 distance
Computational Statistics
Cluster Analysis for Data Mining and System Identification
Cluster Analysis for Data Mining and System Identification
Fuzzy c-means clustering methods for symbolic interval data
Pattern Recognition Letters
An introduction to symbolic data analysis and the SODAS software
Intelligent Data Analysis
Symbolic Data Analysis and the SODAS Software
Symbolic Data Analysis and the SODAS Software
Cluster Analysis
Dynamic clustering of interval-valued data based on adaptive quadratic distances
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Relevance learning in unsupervised vector quantization based on divergences
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Incorporating Fuzzy Membership Functions into the Perceptron Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Clustering of symbolic objects using gravitational approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy clustering for symbolic data
IEEE Transactions on Fuzzy Systems
Fuzzy and hard clustering analysis for thyroid disease
Computer Methods and Programs in Biomedicine
Multiple linear regression modeling for compositional data
Neurocomputing
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The Fuzzy Kohonen Clustering Network combines the idea of fuzzy membership values for learning rates. It is a kind of self-organizing fuzzy neural network that can show great superiority in processing the ambiguity and the uncertainty of data sets or images. Symbolic data analysis provides suitable tools for managing aggregated data described by intervals. This paper introduces Fuzzy Kohonen Clustering Networks for partitioning interval data. The first network is based on a fixed Euclidean distance for interval and the second one considers weighted distances that change at each iteration, but are different from one cluster to another. Experiments with real and synthetic interval data sets demonstrate the usefulness of these networks.