Synonyms Mixture model Definition Model-based clustering is a classification technique where the data is viewed as arising from the underlying mixture of probability distributions with each mixture component representing a cluster. Characteristics Overview Model-based clustering treats data as arising from ...
1. The fitness of cluster model to data distribution is critical to probabilistic-model-based clustering. 在基于概率模型的聚类中,簇模型对数据分布的拟合性直接影响着聚类质量。2) grid-based probabilistic model 基于栅格的概率模型 1. The local map is a grid-based probabilistic model: the work ...
Model-based clustering is a popular technique relying on the notion of finite mixture models that proved to be efficient in modeling heterogeneity in data. The underlying idea is to model each data group by a particular mixture component. This relationship between mixed distributions and clusters for...
aIn the model-based clustering, it is assumed that the data are generated by a mixture of underlying probability distribution, where each component k of the mixture represents a cluster. Thus, the matrix data is assumed to be an i.i.d sample x = (x1; : : : ; xn) from a probability...
This model is an extension of the Latent Class Analysis model, which captures clustering structures among objects. An EM (expectation maximization) algorithm with MM (minorization maximization) steps is developed to perform parameter estimation while a cross validated likelihood approach is employed to ...
In the framework of Bayesian model-based clustering based on a finite mixture of Gaussian distributions, we present a joint approach to estimate the number of mixture components and identify cluster-relevant variables simultaneously as well as to obtain an identified model. Our approach consists in ...
Modeling the evolution of infrared galaxies : clustering of galaxies in the Cosmic Infrared Background Astronomy and AstrophysicsA. Pénin, O. Doré, G. Lagache, M. Béthermin, Modeling the evolution of infrared galaxies: clustering of galaxies in the ... A Pénin,O Doré,G Lagache,... ...
MetAssign: probabilistic annotation of metabolites from LC–MS data using a Bayesian clustering approach The use of liquid chromatography coupled to mass spectrometry has enabled the high-throughput profiling of the metabolite composition of biological samples... R Daly,S Rogers,J Wandy,... - 《Bio...
Model-based clustering and segmentation of time series with changes in regime Mixture model-based clustering, usually applied to multidimensional data, has become a popular approach in many data analysis problems, both for its good s... A Samé,F Chamroukhi,GP Aknin - 《Advances in Data Analys...
Clustering in high-dimensional spaces is nowadays a recurrent problem in many scientific domains but remains a difficult task from both the clustering accuracy and the result understanding points of view. This paper presents a discriminative latent mixture (DLM) model which fits the data in a latent...