Sökning: "regularization"

Visar resultat 1 - 5 av 150 uppsatser innehållade ordet regularization.

1. 1. Predicting Counter-Strike Matches using Machine Learning Models

   Kandidat-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Erik Broms; William Nordansjö; [2024]
   Nyckelord :Mathematics and Statistics;

   Sammanfattning : Sports betting is a widespread industry where predictive modeling play a big role. The goal of this thesis is to explore the possibilities of machine learning within the realm of e-sport prediction. The data used for this thesis is publicly available data was recorded over a three year period. LÄS MER

3. 2. 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

4. 3. Topological regularization and relative latent representations

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Alejandro García Castellanos; [2023]
   Nyckelord :Algebraic Topology; Large Language Models; Relative Representation; Representation Learning; Model Stitching; Topological DataAnalysis; Zero-shot; Algebraisk topologi; Stora språkmodeller; Relativ representation; Representationsinlärning; Modell sömmar; Topologisk dataanalys; Zero-shot;

   Sammanfattning : This Master's Thesis delves into the application of topological regularization techniques and relative latent representations within the realm of zero-shot model stitching. Building upon the prior work of Moschella et al. LÄS MER

5. 4. Data Driven Augmentation for Deep Learning Applications

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Sanna Severinsson; [2023]
   Nyckelord :;

   Sammanfattning : Deep learning models are achieving remarkable performance on numerous tasks across various fields and applications. However, current deep learning models often suffer from overfitting and are therefore heavily reliant on regularization techniques such as data augmentation. LÄS MER

7. 5. Mitigating Unintended Bias in Toxic Comment Detection using Entropy-based Attention Regularization

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Fabio Camerota; [2023]
   Nyckelord :XLNet; BERT; Toxic Comment Classification; Entropy-based Attention Regularization; XLNet; BERT; Toxisk Kommentar Klassificering; Entropibaserad uppmärksamhetsreglering;

   Sammanfattning : The proliferation of hate speech is a growing challenge for social media platforms, as toxic online comments can have dangerous consequences also in real life. There is a need for tools that can automatically and reliably detect hateful comments, and deep learning models have proven effective in solving this issue. LÄS MER