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 ...
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 ...
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 ...
BACKGROUND Leprosy, a neglected tropical disease caused by Mycobacterium leprae, presents significant public health challenges in Brazil due to its slow progression, dermato-neurological ...
About every 10 minutes, it seems, a new article about a "revolutionary breakthrough" in AI hits my screen. A new approach, a new feature, billions of dollars this, AI agents that. It has been non-stop ...
ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...
ABSTRACT: The use of machine learning algorithms to identify characteristics in Distributed Denial of Service (DDoS) attacks has emerged as a powerful approach in cybersecurity. DDoS attacks, which ...
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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