Essays about: "L1 Regularization"

Showing result 1 - 5 of 7 essays containing the words L1 Regularization.

  1. 1. Elastic Net Regression for Prosthesis Control in Short Residual Limb Amputees: Performance and Generalizability

    University essay from Lunds universitet/Avdelningen för Biomedicinsk teknik

    Author : Oskar Berg; [2023]
    Keywords : Neuroengineering; Statistics; Biomedical Signal Processing; Technology and Engineering;

    Abstract : This Master's thesis in Biomedical Engineering investigates the performance and generalizability of linear regression models in context of prosthesis control for short residual limb amputees. This thesis uses intramuscular electromyography data, and a regression and emplys a regression technique called Elastic Net Regression - a technique that combines L1 and L2-regularization - to predict 1-DOF isometric forces outputs from fingers and the wrist. READ MORE

  2. 2. Explainable Machine Learning in Cardiovascular Diagnostics

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Alexander Gutell; Ludvig Skare; [2023]
    Keywords : ;

    Abstract : The major challenges in implementing machine learning models in medical applications stemfrom ethical and accountability concerns, which arise from the lack of insight and understandingof the models' inner workings and reasoning. This opaqueness has resulted in the emergenceof a new subfield of machine learning called Explainability, which aims to develop and deploymethods to gain insight into how input data is weighted and propagated through a machinelearning algorithm. READ MORE

  3. 3. Investigating Relations between Regularization and Weight Initialization in Artificial Neural Networks

    University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

    Author : Rasmus Sjöö; [2022]
    Keywords : Artificial Neural Networks; L1 Regularization; L2 Regularization; Loss Function; Maximum Likelihood; Regularization Strength Synthetic Data Generation; Weight Initialization; Physics and Astronomy;

    Abstract : L2 regularization is a common method used to prevent overtraining in artificial neural networks. However, an issue with this method is that the regularization strength has to be properly adjusted for it to work as intended. This value is usually found by trial and error which can take some time, especially for larger networks. READ MORE

  4. 4. Predicting Subprime Customers' Probability of Default Using Transaction and Debt Data from NPLs

    University essay from KTH/Matematisk statistik

    Author : Lai-Yan Wong; [2021]
    Keywords : Credit Scoring Model; Probability of Default; Payment Behaviour; Subprime Customer; Non-performing Loan; Logistic Regression; Regularization; Feature Selection; Kreditvärdighetsmodell; Sannolikhet för Fallissemang; Betalningsbeteende; Högriskkunder; Nödlidandelån; Logistik Regression; Regularisering; Variabelselektion;

    Abstract : This thesis aims to predict the probability of default (PD) of non-performing loan (NPL) customers using transaction and debt data, as a part of developing credit scoring model for Hoist Finance. Many NPL customers face financial exclusion due to default and therefore are considered as bad customers. READ MORE

  5. 5. Regularization Methods in Neural Networks

    University essay from Uppsala universitet/Statistiska institutionen

    Author : Jacob Kasche; Fredrik Nordström; [2020]
    Keywords : Neural Networks; Overfitting; Regularization methods; MNIST; CIFAR-10;

    Abstract : Overfitting is a common problem in neural networks. This report uses a simple neural network to do simulations relevant for the field of image recognition. In this report, four common regularization methods for dealing with overfitting are evaluated. READ MORE