Browsing by Subject "Clustering"
Now showing items 1-14 of 14
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(Texas A&M University, 2007-09-17)The increased collection of high-dimensional data in various fields has raised a strong interest in clustering algorithms and variable selection procedures. In this disserta- tion, I propose a model-based method that ...
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(Energy Systems Laboratory (http://esl.tamu.edu), 2008-10)The potential to save energy by changing operational parameters - especially in existing commercial buildings – is in the magnitude of 5-30%. In order to realize this saving potential in the long term, continuous commissioning ...
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(Texas A&M University, 2006-08-16)High Dimension, Low Sample Size (HDLSS) problems have received much attention recently in many areas of science. Analysis of microarray experiments is one such area. Numerous studies are on-going to investigate the behavior ...
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(2012-07-16)For open-ended information tasks, users must sift through many potentially relevant documents assessing and prioritizing them based on relevance to current information need, a practice we refer to as document triage. Users ...
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(2018-11-01)Unsupervised and semi-supervised learning are explored in convex clustering with metric learning while supervised learning is explored in a novel feature selection method. First, we evaluate the performance of convex ...
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(2019-04-10)Geometric approximation methods are a preferred solution to handle complexities (such as a large volume or complex features such as concavities) in geometric objects or environments containing them. Complexities often pose ...
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Objective: Identify if principle components analysis and multiple correspondence analysis are suitable dimension reduction techniques for the California Health Interview Survey. Identify which health risk behaviors, mental ...
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(2021-01-06)Traditional photovoltaic materials like silicon are constrained to a planar form factor due to the fragility of the crystalline structure. The third generation of photovoltaics like thin-film provide the benefit of ...
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(Texas A&M University, 2006-10-30)Nonparametric Bayesian models have been researched extensively in the past 10 years following the work of Escobar and West (1995) on sampling schemes for Dirichlet processes. The infinite mixture representation of the ...
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(2023-01-10)Safe and sustainable operations in Geocentric Orbit require the acquisition, tracking, and predictive use of a large amount of data pertaining to the existence, characterization, and orbital state of objects in Earth orbit. ...
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(Texas A&M University, 2006-04-12)Cluster-based information retrieval systems often use a similarity measure to compute the association among text documents. In this thesis, we focus on a class of similarity measures named Query-Sensitive Similarity (QSS) ...
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(2022-04-14)The availability of large-scale spatial and temporal data has fueled increasing interest in statistical modelling and analysis. With the recent development of data collection and data storage techniques, the observation ...
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(2019-07-19)This dissertation is focused on certain clustering and partitioning problems in networks. We present a comprehensive study of the maximum independent union of cliques problem and its generalizations in uniform random graphs. ...
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A novel unsupervised learning-based clustering approach to represent the flamelet tables is developed. The typical tabulation method for flamelet-based modeling generally requires a large amount of storage. A well-developed ...