Essays about: "Imbalanced data classification"

Showing result 1 - 5 of 64 essays containing the words Imbalanced data classification.

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

    University essay from Uppsala universitet/Analys och partiella differentialekvationer

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

    Abstract : 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. READ MORE

  3. 2. Improving echocardiogram view classification using diffusion models

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

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

    Abstract : 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. READ MORE

  4. 3. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

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

    Abstract : 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. READ MORE

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

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

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

    Abstract : 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. READ MORE

  6. 5. Multi-Class Classification for Predicting Customer Satisfaction : Application of machine learning methods to predict customer satisfaction at IKEA

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Stina Backerholm; Malin Börjesjö; [2023]
    Keywords : Multi-Class Classification; Imbalanced Data; Machine Learning; Multi-Klass Klassifisering; Obalanserat Data; Maskininlärning;

    Abstract : Gaining a comprehensive understanding of the features that contribute to customer satisfaction after contact with IKEA’s Remote Customer Meeting Points (RCMPs) is essential for implementing effective remedial measures in the future. The aim of this project is to investigate if it is possible to find key features that influence customer satisfaction and to use these to predict customer satisfaction. READ MORE