Search for dissertations about: "supervised statistical learning"

Showing result 1 - 5 of 19 swedish dissertations containing the words supervised statistical learning.

  2. 1. Visual Analytics for Explainable and Trustworthy Machine Learning

    Author : Angelos Chatzimparmpas; Andreas Kerren; Rafael M. Martins; Ilir Jusufi; Alex Endert; Linnéuniversitetet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; visualization; interaction; visual analytics; explainable machine learning; XAI; trustworthy machine learning; ensemble learning; dimensionality reduction; supervised learning; unsupervised learning; ML; AI; tabular data; visualisering; interaktion; visuell analys; förklarlig maskininlärning; XAI; pålitlig maskininlärning; ensembleinlärning; dimensionesreducering; övervakad inlärning; oövervakad inlärning; ML; AI; tabelldata; Computer Science; Datavetenskap; Informations- och programvisualisering; Information and software visualization;

    Abstract : The deployment of artificial intelligence solutions and machine learning research has exploded in popularity in recent years, with numerous types of models proposed to interpret and predict patterns and trends in data from diverse disciplines. However, as the complexity of these models grows, it becomes increasingly difficult for users to evaluate and rely on the model results, since their inner workings are mostly hidden in black boxes, which are difficult to trust in critical decision-making scenarios. READ MORE

  4. 2. Statistical Feature Selection : With Applications in Life Science

    Author : Roland Nilsson; Jesper Tegnér; Johan Björkegren; Sepp Hochreiter; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine learning; supervised learning; classification; dimemsionality reduction; multiple testing; gene expression; microarray; cancer; Bioinformatics; Bioinformatik;

    Abstract : The sequencing of the human genome has changed life science research in many ways. Novel measurement technologies such as microarray expression analysis, genome-wide SNP typing and mass spectrometry are now producing experimental data of extremely high dimensions. READ MORE

  5. 3. Applied Machine Learning in Steel Process Engineering : Using Supervised Machine Learning Models to Predict the Electrical Energy Consumption of Electric Arc Furnaces

    Author : Leo Carlsson; Pär Jönsson; Peter Samuelsson; Mikael Vejdemo-Johansson; Henrik Saxen; KTH; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Electric Arc Furnace; Electrical Energy Consumption; Statistical Modelling; Machine Learning; Interpretable Machine Learning; Predictive Modelling; Industry 4.0; Ljusbågsugn; Elenergiförbrukning; Statistisk Modellering; Maskininlärning; Tolkningsbar Maskininlärning; Prediktiv Modellering; Industri 4.0; Teknisk materialvetenskap; Materials Science and Engineering; Metallurgical process science; Metallurgisk processvetenskap;

    Abstract : The steel industry is in constant need of improving its production processes. This is partly due to increasing competition and partly due to environmental concerns. One commonly used method for improving these processes is through the act of modeling. READ MORE

  6. 4. Statistical methods in medical image estimation and sparse signal recovery

    Author : Fekadu Lemessa Bayisa; Jun Yu; Ottmar Cronie; Henning Omre; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Computed tomography; magnetic resonance imaging; Gaussian mixture model; skew-Gaussian mixture model; hidden Markov random field; hidden Markov model; supervised statistical learning; synthetic CT images; pseudo-CT images; spike and slab prior; adaptive algorithm;

    Abstract : This thesis presents work on methods for the estimation of computed tomography (CT) images from magnetic resonance (MR) images for a number of diagnostic and therapeutic workflows. The study also demonstrates sparse signal recovery method, which is an intermediate method for magnetic resonance image reconstruction. READ MORE

  7. 5. A Multi-Dimensional Approach to Human Mobility and Transportation Mode Detection Using GPS Data

    Author : Paria Sadeghian; Johan Håkansson; Xiaoyun Zhao; Mengjie Han; Kevin Heaslip; Högskolan Dalarna; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Transport mode detection; Machine learning; Statistical learning; Rule-based method; Data labelling;

    Abstract : GPS tracking data is an essential resource for analyzing human travel patterns and evaluating the effects on transportation systems. The primary challenge, however, is to accurately identify the modes of transportation within unlabeled GPS data. These approaches range from simple rule-based systems to advanced machine-learning techniques. READ MORE