Sökning: "SMOTE"

Visar resultat 1 - 5 av 36 uppsatser innehållade ordet SMOTE.

  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. 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. 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

  5. 4. Optimizing ERP Recommendations Using Machine Learning Techniques

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

    Författare :Ante Jeremiah; [2023]
    Nyckelord :Machine Learning; Imbalanced;

    Sammanfattning : This study explores the application of a recommendation engine in collaboration with Fortnox. The primary focus of this paper is to find potential improvements for their recommendation engine in terms of accurate recommendation for users. LÄS MER

  7. 5. Exploring Alarm Data for Improved Return Prediction in Radios : A Study on Imbalanced Data Classification

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Matematiska institutionen

    Författare :Sofia Färenmark; [2023]
    Nyckelord :Imbalanced data classification; LASSO; Boruta; SVM; RFC; neural network; decision tree; AUC; AUPRC;

    Sammanfattning : The global tech company Ericsson has been tracking the return rate of their products for over 30 years, using it as a key performance indicator (KPI). These KPIs play a critical role in making sound business decisions, identifying areas for improvement, and planning. LÄS MER