Sökning: "machine learning classification"

Visar resultat 1 - 5 av 1178 uppsatser innehållade orden machine learning classification.

  1. 1. Feature Selection for Microarray Data via Stochastic Approximation

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

    Författare :Erik Rosvall; [2024-03-18]
    Nyckelord :feature selection; feature ranking; microarray data; stochastic approximation; Barzilai and Borwein method; Machine Learning; AI;

    Sammanfattning : This thesis explores the challenge of feature selection (FS) in machine learning, which involves reducing the dimensionality of data. The selection of a relevant subset of features from a larger pool has demonstrated its effectiveness in enhancing the performance of various machine learning algorithms. LÄS MER

  3. 2. Predictive Modeling of Pipetting Dynamics. Multivariate Regression Analysis: PLS and ANN for Estimating Density and Volume from Pressure Recordings

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Lisa Linard Pedersen; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Thermo Fisher Scientific manufacture automatic pipetting instruments for diagnostic tests. These tests are sensitive to abnormalities and changes in e.g. volume or density could potentially lead to less precision or other issues in the pipetting work flow. LÄS MER

  4. 3. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Anastasia Sarelli; [2024]
    Nyckelord :Geography; GIS; Land Cover Classification; Landsat; Machine Learning; Earth and Environmental Sciences;

    Sammanfattning : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. LÄS MER

  5. 4. 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

  7. 5. Self-Supervised Learning for Tabular Data: Analysing VIME and introducing Mix Encoder

    Kandidat-uppsats, Lunds universitet/Fysiska institutionen

    Författare :Max Svensson; [2024]
    Nyckelord :Machine Learning; Self-supervised learning; AI; Physics; Medicine; Physics and Astronomy;

    Sammanfattning : We introduce Mix Encoder, a novel self-supervised learning framework for deep tabular data models based on Mixup [1]. Mix Encoder uses linear interpolations of samples with associated pretext tasks to form useful pre-trained representations. LÄS MER