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Infinite Dirichlet mixture models learning via expectation propagation

Fan, Wentao; Bouguila, Nizar - In: Advances in Data Analysis and Classification 7 (2013) 4, pp. 465-489

In this article, we propose a novel Bayesian nonparametric clustering algorithm based on a Dirichlet process mixture of …

Persistent link: https://www.econbiz.de/10010846129

Model-based clustering and segmentation of time series with changes in regime

Samé, Allou; Chamroukhi, Faicel; Govaert, Gérard; … - In: Advances in Data Analysis and Classification 5 (2011) 4, pp. 301-321

Persistent link: https://www.econbiz.de/10009404127

Variable selection in model-based clustering using multilocus genotype data

Toussile, Wilson; Gassiat, Elisabeth - In: Advances in Data Analysis and Classification 3 (2009) 2, pp. 109-134

Persistent link: https://www.econbiz.de/10005015120

A comparison of some criteria for states selection in the latent Markov model for longitudinal data

Bacci, S.; Pandolfi, S.; Pennoni, F. - In: Advances in Data Analysis and Classification 8 (2014) 2, pp. 125-145

We compare different selection criteria to choose the number of latent states of a multivariate latent Markov model for longitudinal data. This model is based on an underlying Markov chain to represent the evolution of a latent characteristic of a group of individuals over time. Then, the...

Persistent link: https://www.econbiz.de/10010846125

A latent class analysis of the public attitude towards the euro adoption in Poland

Genge, Ewa - In: Advances in Data Analysis and Classification 8 (2014) 4, pp. 427-442

Latent class analysis can be viewed as a special case of model–based clustering for multivariate discrete data. It is … target marketing. We used the model based clustering approach for grouping and detecting inhomogeneities of Polish opinions …

Persistent link: https://www.econbiz.de/10011151404

Mixtures of biased sentiment analysers

Salter-Townshend, Michael; Murphy, Thomas - In: Advances in Data Analysis and Classification 8 (2014) 1, pp. 85-103

clustered into either predetermined or data-driven clusters, based on their biases? If so, such a clustering could be used to …. We then demonstrate the clustering that exists in our motivating dataset, namely the analysis of potentially economically …

Persistent link: https://www.econbiz.de/10010758715

A review on consistency and robustness properties of support vector machines for heavy-tailed distributions

Messem, Arnout Van; Christmann, Andreas - In: Advances in Data Analysis and Classification 4 (2010) 2, pp. 199-220

Persistent link: https://www.econbiz.de/10008674106

Variational Bayes approximations for clustering via mixtures of normal inverse Gaussian distributions

Subedi, Sanjeena; McNicholas, Paul - In: Advances in Data Analysis and Classification 8 (2014) 2, pp. 167-193

Parameter estimation for model-based clustering using a finite mixture of normal inverse Gaussian (NIG) distributions …

Persistent link: https://www.econbiz.de/10010794019

Clustering of functional data in a low-dimensional subspace

Yamamoto, Michio - In: Advances in Data Analysis and Classification 6 (2012) 3, pp. 219-247

functional objects and also find an optimal subspace for clustering, simultaneously. The method is based on the k-means criterion … for functional data and seeks the subspace that is maximally informative about the clustering structure in the data. An …

Persistent link: https://www.econbiz.de/10010846119

Estimating common principal components in high dimensions

Browne, Ryan; McNicholas, Paul - In: Advances in Data Analysis and Classification 8 (2014) 2, pp. 217-226

solutions to this problem and are effective in higher dimensions. We use mixture model-based clustering applications to …

Persistent link: https://www.econbiz.de/10010846120