Sökning: "Imbalanced datasets"

Visar resultat 1 - 5 av 34 uppsatser innehållade orden Imbalanced datasets.

  1. 1. Improving echocardiogram view classification using diffusion models

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Luis Arevalo; Anouka Ranby; [2023-10-23]
    Nyckelord :Computer; science; computer science; engineering; project; artificial intelligence; machine learning; deep neural networks; diffusion models; synthetic data; echocardiogram classification;

    Sammanfattning : 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

  3. 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)

    Författare :Li Ang Hu; Long Ma; [2023]
    Nyckelord :Imbalanced datasets; Swedish text financial datasets; Accuracy; Matthews correlation coefficient; Recall; Multinomial Naive Bayes; SMOTE; TomekLinks; Performance optimization;

    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

  4. 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 systemvetenskap

    Författare :Laura Galera Alfaro; [2023]
    Nyckelord :Explainable Artificial Intelligence; Learning To Rank; Local ModelAgnostic Interpretability; Ranking Generalized Additive Models;

    Sammanfattning : 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

  5. 4. Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning

    Master-uppsats, KTH/Matematisk statistik

    Författare :Hannes Andersson; John Sjöberg; [2023]
    Nyckelord :Supply chain disruption; SMOTE; feature engineering; machine learning; random forest; statistics; applied mathematics; Störning i försörjningskedja; maskininlärning; matematik; statistik;

    Sammanfattning : 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

  7. 5. Neural Networks for Predictive Maintenance on Highly Imbalanced Industrial Data

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Oscar Montilla Tabares; [2023]
    Nyckelord :Class Imbalance; Cost Sensitivity; Cost-Sensitive Learning; Focal Loss; Binary Classification; Machine Learning; Deep Learning;

    Sammanfattning : 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