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• W2293175044 abstract "Observing natural phenomena at several levels of detail results in multiresolution data. Extending models and algorithms to cope with multiresolution data is a prerequisite for wide-spread exploitation of the data represented in the multiple resolutions. Mixture models are widely used probabilistic models, however, the mixture models in their standard form can be used to analyze the data represented in a single resolution. In this paper, we propose a multiresolution mixture model based on merging of the mixture components across models represented in dierent resolutions. Result of such an analysis scenario is to have multiple mixture models, one mixture model for each resolution of data. Our proposed solution is based on the idea on the interaction between mixture models. More specically, we repeatedly merge component distributions of mixture models across dierent resolutions. We experiment our proposed algorithm on the two real-world chromosomal aberration datasets represented in two dierent resolutions. Results show an improvement" @default.
• W2293175044 created "2016-06-24" @default.
• W2293175044 creator A5041021330 @default.
• W2293175044 creator A5074593755 @default.
• W2293175044 date "2012-11-17" @default.
• W2293175044 modified "2023-09-24" @default.
• W2293175044 title "Multiresolution Mixture Modeling using Merging of Mixture Components" @default.
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• W2293175044 hasPublicationYear "2012" @default.
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