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- W3082764994 abstract "This chapter deals with the model-based approach to clustering based on a probability model, specifically the Finite Mixture Model (FMM). Within such a framework, the crucial problems of determining the number of clusters and choosing an appropriate clustering method can be seen as a problem of model selection. In this chapter, after a brief introduction to the model-based clustering framework, FMMs will be introduced with particular emphasis on the most commonly used family, namely, the Gaussian, for continuous data. Then, we briefly mention some approaches to model-based clustering for non-continuous data. The analysis of several real-world data will also be discussed." @default.
- W3082764994 created "2020-09-08" @default.
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- W3082764994 date "2020-01-01" @default.
- W3082764994 modified "2023-09-26" @default.
- W3082764994 title "Model-Based Clustering" @default.
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- W3082764994 doi "https://doi.org/10.1007/978-981-13-0553-5_6" @default.
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