Unsupervised Learning of a Finite Discrete Mixture Model Based on the Multinomial Dirichlet Distribution: Application to Texture Modeling
نویسندگان
چکیده
This paper presents a new finite mixture model based on the Multinomial Dirichlet distribution (MDD). For the estimation of the parameters of this mixture we propose an unsupervised algorithm based on the Maximum Likelihood (ML) and Fisher scoring methods. This mixture is used to produce a new texture model. Experimental results concern texture images summarizing and are reported on the Vistex texture image database from the MIT Media Lab.
منابع مشابه
On The Dirichlet Distribution
The Dirichlet distribution is a multivariate generalization of the Beta distribution. It is an important multivariate continuous distribution in probability and statistics. In this report, we review the Dirichlet distribution and study its properties, including statistical and information-theoretic quantities involving this distribution. Also, relationships between the Dirichlet distribution an...
متن کاملMML-Based Approach for Finite Dirichlet Mixture Estimation and Selection
This paper proposes an unsupervised algorithm for learning a finite Dirichlet mixture model. An important part of the unsupervised learning problem is determining the number of clusters which best describe the data. We consider here the application of the Minimum Message length (MML) principle to determine the number of clusters. The Model is compared with results obtained by other selection cr...
متن کاملOnline clustering via finite mixtures of Dirichlet and minimum message length
This paper presents an online algorithm for mixture model-based clustering. Mixture modeling is the problem of identifying and modeling components in a given set of data. The online algorithm is based on unsupervised learning of finite Dirichlet mixtures and a stochastic approach for estimates updating. For the selection of the number of clusters, we use the minimum message length (MML) approac...
متن کاملDirichlet Mixtures in Text Modeling
Word rates in text vary according to global factors such as genre, topic, author, and expected readership (Church and Gale 1995). Models that summarize such global factors in text or at the document level, are called ‘text models.’ A finite mixture of Dirichlet distribution (Dirichlet Mixture or DM for short) was investigated as a new text model. When parameters of a multinomial are drawn from ...
متن کاملUnsupervised Coreference of Publication Venues
Information about the venues of research papers is useful for information retrieval and for automatic mining of the literature. Important to processing venue information is venue coreference, the task of determining which possibly dissimilar mentions of venues refer to the same underlying venue. A natural unsupervised technique for this problem is generative mixture modeling, and indeed such mo...
متن کامل