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 10 of 10 for “"Dimensionality Reduction Method"”.
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On Sequence Clustering and Supervised Dimensionality Reduction
… identically generated random sequences, and 2) dimensionality reduction for classification problems. </p> <p>For sequence clustering, the focus is on large sample performance of classical clustering algorithms, including the k-medoids algorithm and hierarchical agglomerative clustering (HAC) …
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Semi supervised weighted maximum variance dimensionality reduction
… in some scenarios. In those scenarios, the dimensionality reduction methods play a major role for extracting useful features. The two parameter weighted maximum variance (2P-WMV) is a generalized dimensionality reduction method of which principal component analysis (PCA) and maximum margin …
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Genetic Association Mapping : Missing Markers, Epistatic Effects, and Applications
… we first proposed a linkage-based imputation method for missing marker data given available linkage information and then integrated a MDR (multifactor dimensionality reduction) method with a forward variable selection approach. The simulation studies showed that both the proposed linkage-based …
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Addressing geometric abnormalities and algorithmic shortcomings in metagenomic analysis.
… to identify shortcomings in microbiome analysis methods, making maximal use of sequencing data output to accurately represent sample relationships in a microbiome dataset. We introduce LMdist, a dimensionality reduction method for adjusting pairwise distances to more accurately represent …
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Bioinstrumentation and Statistical Methods for Investigating Host-Microbial Interactions
… be simultaneously addressed while reducing its dimensionality. I verify the technique’s performance by comparing it to an existing dimensionality reduction method. Taken together, the combined microfluidic and data analysis approaches developed can help bridge several technological gaps in …
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Defining cell state regulators in cancers using single-cell analysis and CRISPR-Cas9 screening
… cell line models across 22 cancer types [1]. A dimensionality reduction method which resolves continuous expression signatures at multiple resolutions was used to resolve a range of behaviours, from consistent intra-sample cell states to cancer subtypes. In the analysis of melanoma models, three …
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Assessment of Individual Differences in Online Social Networks Using Machine Learning
… this goal is not possible using conventional dimensionality reduction and linear regression models. Here I develop a supervised dimensionality reduction method capable of intelligently selecting only useful parts of data for the relevant prediction at hand which also does not lose variance …
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Topics in conditional causal inference
… framework and some basic causal inference methods relevant to this thesis, then provide a summary of the problems and methods studied in the following chapters. In Chapter 2, we consider testing causal effects in complex experimental designs via conditional randomization tests (CRTs). The …
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Real-time Nonlinear Model Predictive Control: Efficient Methods for Domain Reduction
L'abstract è presente nell'allegato / the abstract is in the attachment
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Building a robust clinical diagnosis support system for childhood cancer using data mining methods
… application to bioinformatics: the diversity and dimensionality of biomedical data. The term ‘big data’ was applied to the clinical domain by Yoo et al. (2014), specifically referring to single nucleotide polymorphism (SNP) and gene expression data. This research thesis focuses on three different …