Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Regularization in discriminant analysis: an overview
Computational Statistics & Data Analysis
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Algorithms for Model-Based Gaussian Hierarchical Clustering
SIAM Journal on Scientific Computing
Mixtures of probabilistic principal component analyzers
Neural Computation
Assessing a Mixture Model for Clustering with the Integrated Completed Likelihood
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modelling high-dimensional data by mixtures of factor analyzers
Computational Statistics & Data Analysis
Robust Cluster Analysis via Mixtures of Multivariate t-Distributions
SSPR '98/SPR '98 Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
A well-conditioned estimator for large-dimensional covariance matrices
Journal of Multivariate Analysis
Subspace clustering for high dimensional data: a review
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Simultaneous Feature Selection and Clustering Using Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Classification of large data sets with mixture models via sufficient EM
Computational Statistics & Data Analysis
Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution
Computational Statistics & Data Analysis
Penalized Model-Based Clustering with Application to Variable Selection
The Journal of Machine Learning Research
Robust mixture modeling using the skew t distribution
Statistics and Computing
An Optimal Set of Discriminant Vectors
IEEE Transactions on Computers
Parsimonious Gaussian mixture models
Statistics and Computing
Variable selection in model-based clustering: A general variable role modeling
Computational Statistics & Data Analysis
Partition clustering of high dimensional low sample size data based on p-values
Computational Statistics & Data Analysis
Penalized factor mixture analysis for variable selection in clustered data
Computational Statistics & Data Analysis
A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
KNN-kernel density-based clustering for high-dimensional multivariate data
Computational Statistics & Data Analysis
Model-based cluster and discriminant analysis with the MIXMOD software
Computational Statistics & Data Analysis
The Remarkable Simplicity of Very High Dimensional Data: Application of Model-Based Clustering
Journal of Classification
Robust mixture modeling using multivariate skew t distributions
Statistics and Computing
Dimension reduction for model-based clustering
Statistics and Computing
Modern Applied Statistics with S
Modern Applied Statistics with S
Extending mixtures of multivariate t-factor analyzers
Statistics and Computing
Intrinsic dimension estimation by maximum likelihood in isotropic probabilistic PCA
Pattern Recognition Letters
Simultaneous model-based clustering and visualization in the Fisher discriminative subspace
Statistics and Computing
Initializing the EM algorithm in Gaussian mixture models with an unknown number of components
Computational Statistics & Data Analysis
EM algorithms for multivariate Gaussian mixture models with truncated and censored data
Computational Statistics & Data Analysis
Theoretical and practical considerations on the convergence properties of the Fisher-EM algorithm
Journal of Multivariate Analysis
Computational aspects of fitting mixture models via the expectation-maximization algorithm
Computational Statistics & Data Analysis
Mixtures of Gaussian wells: Theory, computation, and application
Computational Statistics & Data Analysis
A generative model for rank data based on insertion sort algorithm
Computational Statistics & Data Analysis
A hierarchical modeling approach for clustering probability density functions
Computational Statistics & Data Analysis
Editorial: The 2nd special issue on advances in mixture models
Computational Statistics & Data Analysis
HMM-based hybrid meta-clustering ensemble for temporal data
Knowledge-Based Systems
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Model-based clustering is a popular tool which is renowned for its probabilistic foundations and its flexibility. However, high-dimensional data are nowadays more and more frequent and, unfortunately, classical model-based clustering techniques show a disappointing behavior in high-dimensional spaces. This is mainly due to the fact that model-based clustering methods are dramatically over-parametrized in this case. However, high-dimensional spaces have specific characteristics which are useful for clustering and recent techniques exploit those characteristics. After having recalled the bases of model-based clustering, dimension reduction approaches, regularization-based techniques, parsimonious modeling, subspace clustering methods and clustering methods based on variable selection are reviewed. Existing softwares for model-based clustering of high-dimensional data will be also reviewed and their practical use will be illustrated on real-world data sets.