Sökning: "high-dimensional data"

Visar resultat 1 - 5 av 124 uppsatser innehållade orden high-dimensional data.

  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. Geometry of high dimensional Gaussian data

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

    Författare :Olof Samuel Mossberg; [2024]
    Nyckelord :HDLSS; high dimensional data; stochastic boundedness; asymptotic orthogonality; geometry; multivariate normal distribution; HDLSS; högdimensionell data; stokastisk begränsning; asymptotisk ortogonalitet; geometri; multivariat normalfördelning;

    Sammanfattning : Collected data may simultaneously be of low sample size and high dimension. Such data exhibit some geometric regularities consisting of a single observation being a rotation on a sphere, and a pair of observations being orthogonal. This thesis investigates these geometric properties in some detail. LÄS MER

  4. 3. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods

    Kandidat-uppsats, Lunds universitet/Statistiska institutionen

    Författare :Markus Gerholm; Johan Sörstadius; [2024]
    Nyckelord :Linear regression; high dimensional data; regularization; Bayesian methods; Mathematics and Statistics;

    Sammanfattning : As the amount of high dimensional data becomes increasingly accessible and common, the need for reliable methods to combat problems such as overfitting and multicollinearity increases. Models need to be able to manage large data sets where predictor variables often outnumber the amount of observations. LÄS MER

  5. 4. On Expressing Automotive Maneuvers with SFC

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

    Författare :Zizhuang Cui; Jiacheng Li; [2023-10-05]
    Nyckelord :space-filling curve; Software engineering; software testing; taxonomy;

    Sammanfattning : Conventional methods for testing autonomous driving software often involve dealing with a large number of dimensions, which can complicate the processing and analysis of test datasets. Therefore, there is a pressing need to develop a more efficient approach that is both time and cost-effective. LÄS MER

  7. 5. 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