This repository contains the endterm project for the Mining Massive Data Sets course at Ton Duc Thang University. The project is organized into four main tasks: Hierarchical clustering in a ...
Department of Chemistry, University of Copenhagen, Universitetsparken 5, DK 2100 Copenhagen, Denmark Department of Chemistry, Technical University of Denmark, Kemitorvet 207, DK 2800 Kongens Lyngby, ...
Model-based clustering based on parameterized finite Gaussian mixture models. Models are estimated by EM algorithm initialized by hierarchical model-based agglomerative clustering. The optimal model ...
Polycystic ovary syndrome (PCOS) is a common, but clinically heterogeneous, condition. This study explores PCOS subtypes using two orthogonal statistical analyses of biochemical and anthropometric ...
In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...
Singapore-based AI startup Sapient Intelligence has developed a new AI architecture that can match, and in some cases vastly outperform, large language models (LLMs) on complex reasoning tasks, all ...
A hierarchical clustering approach to dissect behavioral symptoms in early-stage breast cancer (BC).
Autoimmune conditions and ‘breast implant illness’ in breast cancer patients with implant-based breast reconstructions. Proportions of patients with clinically meaningful symptoms by CL at Y1 (may not ...
Abstract: Clustering is a significant method of data analytics in real world environments since human labelling of the data is often costly. Clustering was developed as an alternative to manual ...
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