Bayesian Methods and Mixture Models

This study proposes the best clustering method(s) for different distance measures under two different conditions using the cophenetic correlation coefficient. In the first one, the data has multivariate standard normal distribution without outliers for and the second one is with outliers (5%) for . The proposed method…

• İSMET DOĞAN
• SİNAN SARAÇLI

Clustering is an important topic in pattern recognition. Since only the structure of the data dictates the grouping (unsupervised learning), information theory is an obvious criteria to establish the clustering rule. The paper describes a novel valley seeking clustering algorithm using an information theoretic measure…

• ERHAN GÖKÇAY

To determine the number of clusters in the clustering analysis that has a broad range of applied sciences, such as physics, chemistry, biology, engineering, economics etc., many methods have been proposed in the literature. The aim of this paper is to determine the number of clusters of a dataset in a model-based clus…

• SERKAN AKOĞUL

To determine the number of clusters in the clustering analysis that has a broad range of applied sciences, such as physics, chemistry, biology, engineering, economics etc., many methods have been proposed in the literature. The aim of this paper is to determine the number of clusters of a dataset in a model-based clus…

• MURAT ERİŞOĞLU

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• NAZİF ÇALIŞ

A centred Gaussian model that is Markov with respect to an undirected graph G is characterised by the parameter set of its precision matrices which is the cone M+(G) of positive definite matrices with entries corresponding to the missing edges of G constrained to be equal to zero. In a Bayesian framework, the conjugat…

• ALİYE ATAY

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• MUSTAFA ÇAĞATAY KORKMAZ

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• RAMAZAN ÜNLÜ

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• DERVİŞ KARABOĞA
• EMRAH HANÇER

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• YELİZ MERT KANTAR

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• BİRDAL ŞENOĞLU