Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 8 of 8 for “"Automatic clustering"”.
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Clustering of Leukemia Patients via Gene Expression Data Analysis
… a few genes that are responsible for the clustering. A combined approach of Principal Direction Divisive Partitioning and bisect K-means algorithms is applied to the clustering of the selected leukemia dataset, and both unsupervised and supervised methods are considered in order to get the …
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Concept-based Text Clustering
… a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates …
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Advanced Nonparametric Bayesian Functional Modeling
… to reduce the dimensionality and functional clustering to group similar observations and thus reduce the sample size. The complicated data structures and relations can be easily modeled by a Bayesian hierarchical model, or developed from a more generic one by changing the prior distributions. …
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PetroVis & FractVis: Interactive Visual Exploration of High-dimensional Oil and Gas Data
… which involves (manual) validation of the automatic clustering of the data. The experts focus-group evaluation of PetroVis provided insight into the usefulness of the tool in simplifying the analysis of petrographic data clusters. We conclude this thesis by presenting a set of design …
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Hyperspectral image analysis for questioned historical documents.
… component analysis (ICA) and both supervised and automatic clustering methods to historically significant manuscripts and text VIII such as Leabhar na hUidhre, a 12th century Irish text which was subject to part-erasure and rewriting, a 16th Century pastedown cover, and a multi-ink example typical …
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Fuzzy time series analysis and prediction using swarm optimized hybrid model.
… data as the universe of discourse and the automatic clustering algorithm to cluster the universe of discourse by adjusting the clusters into intervals. Furthermore, the particle swarm optimization algorithm is also examined to improve forecasted accuracy. The proposed method is considered …
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Recurrent-Event Models for Change-Points Detection
… to sample from the posterior distributions. Automatic clustering is expected based on change-points without specifying the number of latent clusters. Based on the Dirichlet process mixture model, three clusters exist among the teenage drivers for the Naturalistic Teenage Driving Study. The …