Sökning: "ensemble learning"

Visar resultat 1 - 5 av 218 uppsatser innehållade orden ensemble learning.

1. 1. Detecting Fraudulent User Behaviour : A Study of User Behaviour and Machine Learning in Fraud Detection

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Analys och partiella differentialekvationer

   Författare :Patrik Gerdelius; Sjönneby Hugo; [2024]
   Nyckelord :Fraud Detection; User Behaviour; Random Forest; PCA; SMOTE;

   Sammanfattning : This study aims to create a Machine Learning model and investigate its performance of detecting fraudulent user behaviour on an e-commerce platform. The user data was analysed to identify and extract critical features distinguishing regular users from fraudulent users. LÄS MER

3. 2. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Marisa Wodrich; [2024]
   Nyckelord :Uncertainty quantification; Deep learning; Breast cancer classification; Trustworthy AI; Point-of-care ultrasound; Mathematics and Statistics;

   Sammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER

4. 3. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment

   Master-uppsats,

   Författare :Venkata Vamsi Challa; [2024]
   Nyckelord :Semantic Segmentation; Scene Classification; Environment Recognition; Machine Learning; Deep Learning; Image Classification; Vision Transformers; SAM Segment Anything Model ; Image Segmentation; Contour-aware semantic segmentation;

   Sammanfattning : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. LÄS MER

5. 4. MetaStackVis: Visually-Assisted Performance Evaluation of Metamodels in Stacking Ensemble Learning

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Ilya Ploshchik; [2023]
   Nyckelord :Visualization; interaction; metamodels; validation metrics; predicted probabilities; stacking; stacked generalization; ensemble learning; machine learning;

   Sammanfattning : Stacking, also known as stacked generalization, is a method of ensemble learning where multiple base models are trained on the same dataset, and their predictions are used as input for one or more metamodels in an extra layer. This technique can lead to improved performance compared to single layer ensembles, but often requires a time-consuming trial-and-error process. LÄS MER

7. 5. Unsupervised Online Anomaly Detection in Multivariate Time-Series

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Datorteknik

   Författare :Ludvig Segerholm; [2023]
   Nyckelord :unsupervised; online; anomaly detection; explainable ai; machine learning; mahalanobis distance;

   Sammanfattning : This research aims to identify a method for unsupervised online anomaly detection in multivariate time series in dynamic systems in general and on the case study of Devwards IoT-system in particular. A requirement of the solution is its explainability, online learning and low computational expense. LÄS MER