Sökning: "Imbalanced Datasets"
Visar resultat 1 - 5 av 34 uppsatser innehållade orden Imbalanced Datasets.
1. Improving echocardiogram view classification using diffusion models
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : In the field of medical science datasets are often highly imbalanced, where rare datapoints are of high importance. This study aims to explore the usage of synthetic datasets to improve the classification of echocardiogram views. LÄS MER
2. Optimising Machine Learning Models for Imbalanced Swedish Text Financial Datasets: A Study on Receipt Classification : Exploring Balancing Methods, Naive Bayes Algorithms, and Performance Tradeoffs
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Sammanfattning : This thesis investigates imbalanced Swedish text financial datasets, specifically receipt classification using machine learning models. The study explores the effectiveness of under-sampling and over-sampling methods for Naive Bayes algorithms, collaborating with Fortnox for a controlled experiment. LÄS MER
3. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. LÄS MER
4. Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning
Master-uppsats, KTH/Matematisk statistikSammanfattning : The dairy business is vulnerable to supply chain disruptions since large safety stocks to cover up losses are not always a viable option, therefore it is crucial to maintain a smooth supply chain to ensure stable delivery accuracies. Disruptions are unpredictable and hard to avoid in the supply chain, especially in cases where production errors cause lost production volume. LÄS MER
5. Neural Networks for Predictive Maintenance on Highly Imbalanced Industrial Data
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Preventive maintenance plays a vital role in optimizing industrial operations. However, detecting equipment needing such maintenance using available data can be particularly challenging due to the class imbalance prevalent in real-world applications. LÄS MER