Gaussian mixture models with eigen-decomposed covariance structures make up the most popular family of mixture models for clustering and classification, i.e., the Gaussian parsimonious clustering models (GPCM). Although the GPCM family has been used for almost 20 years, selecting the best member of the family in a given situation remains a troublesome problem. Likelihood ratio tests are develop...

assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. sspco optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. one of the things that smart algorithms are applied to solve is the problem ...

We introduce a family of unsupervised algorithms, numerical taxonomy clustering, to simultaneously cluster data, and to learn a taxonomy that encodes the relationship between the clusters. The algorithms work by maximizing the dependence between the taxonomy and the original data. The resulting taxonomy is a more informative visualization of complex data than simple clustering; in addition, tak...

This study aims to explore and examine the conjectures surrounding the utilization of family planning services among currently married couples of childbearing age in Renk County. This study has adopted a qualitative method to collect data on factors affecting the utilization of family planning services through focus group discussions and in-depth interviews, in rural and urban areas of Renk Cou...

In this research we applied Local Cluster Analysis (LCA) in tandem with Part-of-Speech tagging to monolingual task. We study different Persian POS tags and select a set of designated tags to reduce the size of our index and store the rich content of the documents. In addition, we applied LCA on the retrieved documents to detect the relevant and irrelevant documents to the user query. The cluste...