Sökning: "K-means"
Visar resultat 6 - 10 av 277 uppsatser innehållade ordet K-means.
6. Mathematical modelling simulation data and artificial intelligence for the study of tumour-macrophage interaction
Magister-uppsats, Högskolan i Skövde/Institutionen för biovetenskapSammanfattning : The study explores the integration of mathematical modelling and machine learning to understand tumour-macrophage interactions in the tumour microenvironment. It details mathematical models based on biochemistry and physics for predicting tumour dynamics, highlighting the role of macrophages. LÄS MER
7. The deductibles impact on the risk premium
Master-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistikSammanfattning : The aim of this master thesis is to derive methods that assesses the impact the deductiblehas on the risk premium of an insurance contract. The additive structure of a deductiblenecessitates approaches beyond treating it as a regular covariate in a generalized linearmodel for predicting the risk premium. LÄS MER
8. Active learning for text classification in cyber security
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In the domain of cyber security, machine learning promises advanced threat detection. However, the volume of available unlabeled data poses challenges for efficient data management. This study investigates the potential for active learning, a subset of interactive machine learning, to reduce the effort required for manual data labelling. LÄS MER
9. Domain Knowledge and Representation Learning for Centroid Initialization in Text Clustering with k-Means : An exploratory study
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Text clustering is a problem where texts are partitioned into homogeneous clusters, such as partitioning them based on their sentiment value. Two techniques to address the problem are representation learning, in particular language representation models, and clustering algorithms. LÄS MER
10. Exploring Advanced Clustering Techniques for Business Descriptions : A Comparative Study and Analysis of DBSCAN, K-Means, and Hierarchical Clustering
Uppsats för yrkesexamina på avancerad nivå, Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)Sammanfattning : In this study, we introduce several approaches to analyze large volumes of business descriptions by applying machine learning clustering and classification algorithms. The goal is to efficiently classify these descriptions, reducing the search scope and allowing for better business insights and decision-making processes. LÄS MER