Sökning: "classification algorithm"

Visar resultat 1 - 5 av 543 uppsatser innehållade orden classification algorithm.

  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. Decision Trees for Classification of Repeated Measurements

    Kandidat-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

    Författare :Julianna Holmberg; [2024]
    Nyckelord :Repeated Measurement Data; Growth Curve Model; Linear Discriminant Analysis; Decision Tree; Bootstrap Aggregating; CART; CART-LC;

    Sammanfattning : Classification of data from repeated measurements is useful in various disciplines, for example that of medicine. This thesis explores how classification trees (CART) can be used for classifying repeated measures data. LÄS MER

  4. 3. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Marisa Wodrich; [2024]
    Nyckelord :Uncertainty quantification; Deep learning; Breast cancer classification; Trustworthy AI; Point-of-care ultrasound; Mathematics and Statistics;

    Sammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER

  5. 4. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network : Bildklassificering för hjärntumör medhjälp av förtränat konvolutionell tneuralt nätverk

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Ahmad Osman; Bushra Alsabbagh; [2023]
    Nyckelord :Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

    Sammanfattning : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells inthe brain. The brain is responsible for regulating the functions of all other organs,hence, any atypical growth of cells in the brain can have severe implications for itsfunctions. The number of global mortality in 2020 led by cancerous brains was estimatedat 251,329. LÄS MER

  7. 5. 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