Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: There are two open problems when finite mixture densities are used to model multivariate data: the selection of the number of components and the initialization. ,  propose an online (recursive) algorithm that estimates the parameters of the mixture and that simultaneously selects the number of components. The new algorithm starts with a large number of randomly initialized components. A prior is used as a bias for maximally structured models. A stochastic approximation recursive learning algorithm is proposed to search for the maximum a posteriori (MAP) solution and to discard the irrelevant components.
['Zoran Zivkovic', 'van der Heijden']
I am writing a research paper on a idea Recursive unsupervised learning of finite mixture models
[{"from": "human", "value": "I am writing a research paper on a idea Recursive unsupervised learning of finite mixture models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: There are two open problems when finite mixture densities are used to model multivariate data: the selection of the number of components and the initialization. ,  propose an online (recursive) algorithm that estimates the parameters of the mixture and that simultaneously selects the number of components. The new algorithm starts with a large number of randomly initialized components. A prior is used as a bias for maximally structured models. A stochastic approximation recursive learning algorithm is proposed to search for the maximum a posteriori (MAP) solution and to discard the irrelevant components."}]