Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  deals with the selection of cluster number in a clustering problem taking into account the sideinformation that some points of a chunklet arise from a same cluster. An Expectation-Maximization algorithm is used to estimate the parameters of a mixture model and determine the data partition. To select the number of clusters, usual criteria are not suitable because they do not consider the side-information in the data. Thus  propose suitable criteria which are modified version of three usual criteria, the bayesian information criterion (BIC), the Akaike information criterion (AIC), and the entropy criterion (NEC). The proposed criteria are used to select the number of clusters in the case of two simulated problems and one real problem. Their performances are compared and the influence of the chunklet size is discussed.
['Edith Grall-Maës', 'Duc Tung Dao']
I am writing a research paper on a idea Assessing the Number of Clusters in a Mixture Model with Side-information
[{"from": "human", "value": "I am writing a research paper on a idea Assessing the Number of Clusters in a Mixture Model with Side-information"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  deals with the selection of cluster number in a clustering problem taking into account the sideinformation that some points of a chunklet arise from a same cluster. An Expectation-Maximization algorithm is used to estimate the parameters of a mixture model and determine the data partition. To select the number of clusters, usual criteria are not suitable because they do not consider the side-information in the data. Thus  propose suitable criteria which are modified version of three usual criteria, the bayesian information criterion (BIC), the Akaike information criterion (AIC), and the entropy criterion (NEC). The proposed criteria are used to select the number of clusters in the case of two simulated problems and one real problem. Their performances are compared and the influence of the chunklet size is discussed."}]