Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Alzheimer’s disease (1)
- Computer-aided diagnosis (1)
- Correlation (1)
- Dimensionality reduction (1)
- Disorder (1)
-
- Eukaryotes (1)
- Evolution (1)
- Information Filtering (1)
- Mild cognitive impairment (MCI) (1)
- Monte Carlo Simulation (1)
- Multiclass classification (1)
- Multicollinearity (1)
- Multimodal analysis (1)
- Natural language processing (NLP) (1)
- Orthology (1)
- Paralogy (1)
- Point-of-Interest Recommendation (1)
- Poisson (1)
- Poisson Regression (1)
- Poisson Ridge Regression (1)
- Protein (1)
- Rates (1)
- Recommendation System (1)
- Ridge Regression (1)
- Sequence (1)
- Social Network Analysis (1)
- Statistics (1)
- Structure (1)
Articles 1 - 4 of 4
Full-Text Articles in Statistical Models
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
FIU Electronic Theses and Dissertations
Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …
Computational Analysis Of Large-Scale Trends And Dynamics In Eukaryotic Protein Family Evolution, Joseph Boehm Ahrens
Computational Analysis Of Large-Scale Trends And Dynamics In Eukaryotic Protein Family Evolution, Joseph Boehm Ahrens
FIU Electronic Theses and Dissertations
The myriad protein-coding genes found in present-day eukaryotes arose from a combination of speciation and gene duplication events, spanning more than one billion years of evolution. Notably, as these proteins evolved, the individual residues at each site in their amino acid sequences were replaced at markedly different rates. The relationship between protein structure, protein function, and site-specific rates of amino acid replacement is a topic of ongoing research. Additionally, there is much interest in the different evolutionary constraints imposed on sequences related by speciation (orthologs) versus sequences related by gene duplication (paralogs). A principal aim of this dissertation is to …
Context-Aware Personalized Point-Of-Interest Recommendation System, Ramesh Raj Baral
Context-Aware Personalized Point-Of-Interest Recommendation System, Ramesh Raj Baral
FIU Electronic Theses and Dissertations
The increasing volume of information has created overwhelming challenges to extract the relevant items manually. Fortunately, the online systems, such as e-commerce (e.g., Amazon), location-based social networks (LBSNs) (e.g., Facebook) among many others have the ability to track end users' browsing and consumption experiences. Such explicit experiences (e.g., ratings) and many implicit contexts (e.g., social, spatial, temporal, and categorical) are useful in preference elicitation and recommendation. As an emerging branch of information filtering, the recommendation systems are already popular in many domains, such as movies (e.g., YouTube), music (e.g., Pandora), and Point-of-Interest (POI) (e.g., Yelp).
The POI domain has many …
On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar
On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar
FIU Electronic Theses and Dissertations
Multiple regression models play an important role in analyzing and making predictions about data. Prediction accuracy becomes lower when two or more explanatory variables in the model are highly correlated. One solution is to use ridge regression. The purpose of this thesis is to study the performance of available ridge regression estimators for Poisson regression models in the presence of moderately to highly correlated variables. As performance criteria, we use mean square error (MSE), mean absolute percentage error (MAPE), and percentage of times the maximum likelihood (ML) estimator produces a higher MSE than the ridge regression estimator. A Monte Carlo …