Gogebakan, MarufErol, Hamza2023-04-072023-04-072020978-3-030-36178-5978-3-030-36177-82367-4512WOS:000678771000043https://doi.org/10.1007/978-3-030-36178-5_43https://hdl.handle.net/20.500.12573/1572In this study, a new algorithm was developed for clustering multivariate big data. Normal mixture distributions are used to determine the partitions of variables. Normal mixture models obtained from the partitions of variables are generated using Genetic Algorithms (GA). Each partition in the variables corresponds to a clustering center in the normal mixture model. The best model that fits the data structure from normal mixture models is obtained by using the information criteria obtained from normal mixture distributions.enginfo:eu-repo/semantics/closedAccessGenetic AlgorithmGaussian mixture modelsModel based clusteringInformation criteriaother43539543