I denne oppgaven har jeg sett på Tikhonov-regulasisering av regresjons- og klassifikasjonsproblemer og sammeliknet egne og veileders Matlab-script med andre regresjonsog klassifikasjonsmetoder med hensyn på tidsbruk og ...

In this thesis, we evaluated the performance of two generative models, Conditional Tabular Generative Adversarial Network (CTGAN) and Tabular Variational Autoencoder (TVAE), from the open-source library Synthetic Data Vault ...

Modern data acquisition techniques in healthcare generate large collections of data from multiple sources, such as novel diagnosis and treatment methodologies. Some concrete examples are electronic healthcare record systems, ...

Machine learning is a hot topic in today's society. Data sets of varying sizes show up in a number of contexts, and learning from data sets is important for answering many questions. There is a plethora of methods that can ...

Data analysis methods based on machine- and deep learning approaches are continuously replacing traditional methods. Models based on deep learning (DL) are applicable to many problems and often have better prediction ...

Inspired by the success of deep learning techniques in dense-label prediction and the increasing availability of high precision airborne light detection and ranging (LiDAR) data, we present a research process that compares ...