Clustering: A neural network approach

Authors:
K. -L. Du
Affiliations:
Department of Electrical and Computer Engineering, Concordia University, 1455 de Maisonneuve West, Montreal, Canada, H3G 1M8
Venue:
Neural Networks
Year:
2010

Citing 123
Cited 11

A massively parallel architecture for a self-organizing neural pattern recognition machine

Computer Vision, Graphics, and Image Processing
The ART of Adaptive Pattern Recognition by a Self-Organizing Neural Network

Computer
Unsupervised Optimal Fuzzy Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-organization and associative memory: 3rd edition

Self-organization and associative memory: 3rd edition
Competitive learning algorithms for vector quantization

Neural Networks
A deterministic annealing approach to clustering

Pattern Recognition Letters
On the K-winners-take-all-network

Advances in neural information processing systems 1
Winner-take-all networks of O(N) complexity

Advances in neural information processing systems 1
An analog self-organizing neural network chip

Advances in neural information processing systems 1
Learning internal representations by error propagation

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Clustering characterization of adaptive resonance

Neural Networks
Art 2-A: an adaptive resonance algorithm for rapid category learning and recognition

Neural Networks
A Validity Measure for Fuzzy Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
Development and spatial structure of cortical feature maps: a model study

NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Characterization and detection of noise in clustering

Pattern Recognition Letters
ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network

Neural Networks
Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system

Neural Networks
Graphs: theory and algorithms

Graphs: theory and algorithms
A Classification EM algorithm for clustering and two stochastic versions

Computational Statistics & Data Analysis - Special issue on optimization techniques in statistics
On a class of fuzzy classification maximum likelihood procedures

Fuzzy Sets and Systems
Topology representing networks

Neural Networks
Fuzzy competitive learning

Neural Networks
Growing cell structures—a self-organizing network for unsupervised and supervised learning

Neural Networks
Fuzzy clustering of elliptic ring-shaped clusters

Pattern Recognition Letters
Adaptive Hamming net: a fast-learning ART 1 model without searching

Neural Networks
Two soft relatives of learning vector quantization

Neural Networks
Gaussian ARTMAP: a neural network for fast incremental learning of noisy multidimensional maps

Neural Networks
BIRCH: an efficient data clustering method for very large databases

SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
The World-Wide Web: quagmire or gold mine?

Communications of the ACM
A modified ART 1 algorithm more suitable for VLSI implementations

Neural Networks
Self-organisation in Kohonen's SOM

Neural Networks
Learning vector quantization with training count (LVQTC)

Neural Networks
Distributed learning, recognition, and prediction by ART and ARTMAP neural networks

Neural Networks
Connection between fuzzy theory, simulated annealing, and convex duality

Fuzzy Sets and Systems
Fast fuzzy clustering

Fuzzy Sets and Systems
ARTMAP-IC and medical diagnosis: instance counting and inconsistent cases

Neural Networks
Nonlinear component analysis as a kernel eigenvalue problem

Neural Computation
A Robust Competitive Clustering Algorithm With Applications in Computer Vision

IEEE Transactions on Pattern Analysis and Machine Intelligence
Data clustering: a review

ACM Computing Surveys (CSUR)
Cure: an efficient clustering algorithm for large databases

Information Systems
A Modified Version of the K-Means Algorithm with a Distance Based on Cluster Symmetry

IEEE Transactions on Pattern Analysis and Machine Intelligence
Life-long learning cell structures —continuously learning without catastrophic interference

Neural Networks
The enhanced LBG algorithm

Neural Networks
Principal Direction Divisive Partitioning

Data Mining and Knowledge Discovery
Projective ART for clustering data sets in high dimensional spaces

Neural Networks
The LBG-U Method for Vector Quantization – an Improvement over LBGInspired from Neural Networks

Neural Processing Letters
Fuzzy Clustering Using A Compensated Fuzzy Hopfield Network

Neural Processing Letters
Chameleon: Hierarchical Clustering Using Dynamic Modeling

Computer
Detection and Separation of Ring-Shaped Clusters Using Fuzzy Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Least Biased Fuzzy Clustering Method

IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient k-Means Clustering Algorithm: Analysis and Implementation

IEEE Transactions on Pattern Analysis and Machine Intelligence
An evolutionary technique based on K-means algorithm for optimal clustering in RN

Information Sciences—Applications: An International Journal
A Self-Organizing Network that Can Follow Non-stationary Distributions

ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
On the quality of ART1 text clustering

Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Towards a robust fuzzy clustering

Fuzzy Sets and Systems - Data analysis
k-means: a new generalized k-means clustering algorithm

Pattern Recognition Letters
A Fast Simplified Fuzzy ARTMAP Network

Neural Processing Letters
A Novel Kernel Method for Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
A kernel-based subtractive clustering method

Pattern Recognition Letters
Recursive self-organizing network models

Neural Networks - 2004 Special issue: New developments in self-organizing systems
SOM-based algorithms for qualitative variables

Neural Networks - 2004 Special issue: New developments in self-organizing systems
Adapting k-means for supervised clustering

Applied Intelligence
An incremental network for on-line unsupervised classification and topology learning

Neural Networks
Neural Networks in a Softcomputing Framework

Neural Networks in a Softcomputing Framework
Improving RBF networks performance in regression tasks by means of a supervised fuzzy clustering

Neurocomputing
Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters

IEEE Transactions on Computers
Fast learning in networks of locally-tuned processing units

Neural Computation
Merge SOM for temporal data

Neurocomputing
A Cluster Separation Measure

IEEE Transactions on Pattern Analysis and Machine Intelligence
Competitive learning and soft competition for vector quantizerdesign

IEEE Transactions on Signal Processing
Fuzzy clustering with partial supervision

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Some new indexes of cluster validity

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic K-means algorithm

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A survey of fuzzy clustering algorithms for pattern recognition. II

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy c-means clustering of incomplete data

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An approach to online identification of Takagi-Sugeno fuzzy models

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust clustering methods: a unified view

IEEE Transactions on Fuzzy Systems
Fuzzy shell clustering algorithms in image processing: fuzzy C-rectangular and 2-rectangular shells

IEEE Transactions on Fuzzy Systems
An integrated approach to fuzzy learning vector quantization and fuzzy c-means clustering

IEEE Transactions on Fuzzy Systems
Alternating cluster estimation: a new tool for clustering and function approximation

IEEE Transactions on Fuzzy Systems
Fuzzy order statistics and their application to fuzzy clustering

IEEE Transactions on Fuzzy Systems
Hierarchical unsupervised fuzzy clustering

IEEE Transactions on Fuzzy Systems
Clustering algorithms based on volume criteria

IEEE Transactions on Fuzzy Systems
Generalized fuzzy c-means clustering strategies using Lp norm distances

IEEE Transactions on Fuzzy Systems
Reducing the time complexity of the fuzzy c-means algorithm

IEEE Transactions on Fuzzy Systems
Fuzzy clustering with volume prototypes and adaptive cluster merging

IEEE Transactions on Fuzzy Systems
Robust fuzzy clustering of relational data

IEEE Transactions on Fuzzy Systems
A new kernel-based fuzzy clustering approach: support vector clustering with cell growing

IEEE Transactions on Fuzzy Systems
Generalized weighted conditional fuzzy clustering

IEEE Transactions on Fuzzy Systems
Optimality test for generalized FCM and its application to parameter selection

IEEE Transactions on Fuzzy Systems
A possibilistic approach to clustering

IEEE Transactions on Fuzzy Systems
Fuzzy min-max neural networks -- Part 2: Clustering

IEEE Transactions on Fuzzy Systems
Asymptotically optimal block quantization

IEEE Transactions on Information Theory
Vector quantization with complexity costs

IEEE Transactions on Information Theory
Neural networks for vector quantization of speech and images

IEEE Journal on Selected Areas in Communications
A self-organizing network for hyperellipsoidal clustering (HEC)

IEEE Transactions on Neural Networks
Repairs to GLVQ: a new family of competitive learning schemes

IEEE Transactions on Neural Networks
A methodology for constructing fuzzy algorithms for learning vector quantization

IEEE Transactions on Neural Networks
Growing radial basis neural networks: merging supervised and unsupervised learning with network growth techniques

IEEE Transactions on Neural Networks
Conditional fuzzy clustering in the design of radial basis function neural networks

IEEE Transactions on Neural Networks
A class of competitive learning models which avoids neuron underutilization problem

IEEE Transactions on Neural Networks
Analysis for a class of winner-take-all model

IEEE Transactions on Neural Networks
An axiomatic approach to soft learning vector quantization and clustering

IEEE Transactions on Neural Networks
Clustering of the self-organizing map

IEEE Transactions on Neural Networks
Another K-winners-take-all analog neural network

IEEE Transactions on Neural Networks
Analysis of input-output clustering for determining centers of RBFN

IEEE Transactions on Neural Networks
A new clustering technique for function approximation

IEEE Transactions on Neural Networks
Self-splitting competitive learning: a new on-line clustering paradigm

IEEE Transactions on Neural Networks
Mercer kernel-based clustering in feature space

IEEE Transactions on Neural Networks
Soft learning vector quantization and clustering algorithms based on non-Euclidean norms: multinorm algorithms

IEEE Transactions on Neural Networks
Branching competitive learning Network: A novel self-creating model

IEEE Transactions on Neural Networks
Modified ART 2A growing network capable of generating a fixed number of nodes

IEEE Transactions on Neural Networks
Survey of clustering algorithms

IEEE Transactions on Neural Networks
The fuzzy c spherical shells algorithm: A new approach

IEEE Transactions on Neural Networks
Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps

IEEE Transactions on Neural Networks
Fuzzy min-max neural networks. I. Classification

IEEE Transactions on Neural Networks
Generalized clustering networks and Kohonen's self-organizing scheme

IEEE Transactions on Neural Networks
`Neural-gas' network for vector quantization and its application to time-series prediction

IEEE Transactions on Neural Networks
Rival penalized competitive learning for clustering analysis, RBF net, and curve detection

IEEE Transactions on Neural Networks
Self-creating and organizing neural networks

IEEE Transactions on Neural Networks
Optimal adaptive k-means algorithm with dynamic adjustment of learning rate

IEEE Transactions on Neural Networks
K-winners-take-all circuit with O(N) complexity

IEEE Transactions on Neural Networks
ART-EMAP: A neural network architecture for object recognition by evidence accumulation

IEEE Transactions on Neural Networks

A new approach for multimodel identification of complex systems based on both neural and fuzzy clustering algorithms

Engineering Applications of Artificial Intelligence
Design of fuzzy rule-based classifiers with semantic cointension

Information Sciences: an International Journal
Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Expert Systems with Applications: An International Journal
Growing Self-Organizing Map with cross insert for mixed-type data clustering

Applied Soft Computing
Generation of a clustering ensemble based on a gravitational self-organising map

Neurocomputing
An Automated Workforce Clustering Method for Business Process Reengineering in Research and Development Organizations

International Journal of Information Technology Project Management
Visualizing clusters in artificial neural networks using Morse theory

Advances in Artificial Neural Systems
A new back-propagation neural network optimized with cuckoo search algorithm

ICCSA'13 Proceedings of the 13th international conference on Computational Science and Its Applications - Volume 1
An online self-adaptive modular neural network for time-varying systems

Neurocomputing
Self-Organizing Hidden Markov Model Map (SOHMMM)

Neural Networks
Robust support vector machine-trained fuzzy system

Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

Clustering is a fundamental data analysis method. It is widely used for pattern recognition, feature extraction, vector quantization (VQ), image segmentation, function approximation, and data mining. As an unsupervised classification technique, clustering identifies some inherent structures present in a set of objects based on a similarity measure. Clustering methods can be based on statistical model identification (McLachlan & Basford, 1988) or competitive learning. In this paper, we give a comprehensive overview of competitive learning based clustering methods. Importance is attached to a number of competitive learning based clustering neural networks such as the self-organizing map (SOM), the learning vector quantization (LVQ), the neural gas, and the ART model, and clustering algorithms such as the C-means, mountain/subtractive clustering, and fuzzy C-means (FCM) algorithms. Associated topics such as the under-utilization problem, fuzzy clustering, robust clustering, clustering based on non-Euclidean distance measures, supervised clustering, hierarchical clustering as well as cluster validity are also described. Two examples are given to demonstrate the use of the clustering methods.