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 “"cluster validation"”.
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Bayesian cluster validation
… based on Bayesian principles for validating clusterings and present efficient algorithms for use with centroid or exemplar based clustering solutions. Our framework treats the data as fixed and introduces perturbations into the clustering procedure. In our algorithms, we scale the distances …
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Exploratory Study of Fuzzy Clustering and Set-Distance Based Validation Indexes
This thesis is concerned with issues related to clustering. In particular, it addresses the con-vergence speed of fuzzy c-means family of algorithms and cluster validation. The fuzzy c-meansclustering algorithm and its objective function is studied along with a literature review of thespeed of …
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Neuroengineering of Clustering Algorithms
<p>"Cluster analysis can be broadly divided into multivariate data visualization, clustering algorithms, and cluster validation. This dissertation contributes neural network-based techniques to perform all three unsupervised learning tasks. Particularly, the first paper provides a comprehensive …
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A Distance-Based Clustering Framework for Categorical Time Series: A Case Study in Episodes of Care Healthcare Delivery System
… by equating it to the number of reproducible clusters found. This research proposes a methodological framework to detect reproducible clusters in an unsupervised problem where the true number of clusters is unknown. The proposed framework utilizes k-medoids clustering as it accommodates …
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Robust techniques and applications in fuzzy clustering
… and outliers of least squares minimization based clustering techniques, such as Fuzzy c-Means (FCM) and its variants is addressed. In this work, two novel and robust clustering schemes are presented and analyzed in detail. They approach the problem of robustness from different perspectives. The …
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Computational analysis of gene expression data
… analysis methods. As such, a large number of clustering approaches have been proposed for the analysis of gene expression data obtained from microarray experiments, and consequently, confusion regarding the best approach to take. Common techniques applied are not necessarily the most …
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Analysis of Molecular Dynamics Simulations of Protein Folding
… and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) …
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Modul shlukové analýzy systému pro dolování z dat
Tato diplomová práce se zabývá vývojem modulu pro systém dolování z dat, jenž je vyvíjen na FIT. První část se věnuje obecnému procesu získávání znalostí a shlukové analýze včetně validace shluků, popisuje také Oracle Data Mining včetně algoritmů, které používá pro shlukování. Na závěr představuje …