Algorithms for clustering data
Algorithms for clustering data
Some representations of the multivariate Bernoulli and binomial distributions
Journal of Multivariate Analysis
A Combined Latent Class and Trait Model for the Analysis and Visualization of Discrete Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new Bayesian tree learning method with reduced time and space complexity
Fundamenta Informaticae
How to make large self-organizing maps for nonvectorial data
Neural Networks - New developments in self-organizing maps
Beyond Independence: Probabilistic Models for Query Approximation on Binary Transaction Data
IEEE Transactions on Knowledge and Data Engineering
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
Maximum Likelihood Topographic Map Formation
Neural Computation
Introduction: Special issue on neural networks and kernel methods for structured domains
Neural Networks - Special issue on neural networks and kernel methods for structured domains
On-line EM Algorithm for the Normalized Gaussian Network
Neural Computation
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
A Dirichlet process mixture model for the analysis of correlated binary responses
Computational Statistics & Data Analysis
Bayesian multivariate Poisson mixtures with an unknown number of components
Statistics and Computing
3D head model retrieval in kernel feature space using HSOM
Pattern Recognition
Extracting a diagnostic gait signature
Pattern Recognition
Assessing multivariate Bernoulli models for information retrieval
ACM Transactions on Information Systems (TOIS)
A hybrid artificial immune system and Self Organising Map for network intrusion detection
Information Sciences: an International Journal
Neighborhood rough set based heterogeneous feature subset selection
Information Sciences: an International Journal
Ranking Categorical Features Using Generalization Properties
The Journal of Machine Learning Research
Identifiability of extended latent class models with individual covariates
Computational Statistics & Data Analysis
Canonical representation of conditionally specified multivariate discrete distributions
Journal of Multivariate Analysis
Limits of learning about a categorical latent variable under prior near-ignorance
International Journal of Approximate Reasoning
Document analysis and visualization with zero-inflated poisson
Data Mining and Knowledge Discovery
Attribute reduction and optimal decision rules acquisition for continuous valued information systems
Information Sciences: an International Journal
Exploiting data topology in visualization and clustering of self-organizing maps
IEEE Transactions on Neural Networks
Model-based clustering by probabilistic self-organizing maps
IEEE Transactions on Neural Networks
Probabilistic PCA self-organizing maps
IEEE Transactions on Neural Networks
Multivariate Student-t self-organizing maps
Neural Networks
Self-organizing mixture models
Neurocomputing
Generative and Discriminative Learning by CL-Net
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
AdaBoost-Based Algorithm for Network Intrusion Detection
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Approximating discrete probability distributions with dependence trees
IEEE Transactions on Information Theory
Self-organizing maps, vector quantization, and mixture modeling
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Derivation of a class of training algorithms
IEEE Transactions on Neural Networks
Generalizing self-organizing map for categorical data
IEEE Transactions on Neural Networks
Stochastic approximation for background modelling
Computer Vision and Image Understanding
A novel self-adaptive clustering algorithm for dynamic data
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Expert Systems with Applications: An International Journal
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We present a self-organizing map model to study qualitative data (also called categorical data). It is based on a probabilistic framework which does not assume any prespecified distribution of the input data. Stochastic approximation theory is used to develop a learning rule that builds an approximation of a discrete distribution on each unit. This way, the internal structure of the input dataset and the correlations between components are revealed without the need of a distance measure among the input values. Experimental results show the capabilities of the model in visualization and unsupervised learning tasks.