Search for dissertations about: "dissertation for alternative learning system"

Showing result 1 - 5 of 12 swedish dissertations containing the words dissertation for alternative learning system.

  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. On the Metric-based Approach to Supervised Concept Learning

    Author : Niklas Lavesson; Sweden Karlskrona Blekinge Institute of Technology School of Engineering Department of Systems and Software Engineering; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; classifier evaluation; supervised learning; metric; criteria;

    Abstract : A classifier is a piece of software that is able to categorize objects for which the class is unknown. The task of automatically generating classifiers by generalizing from examples is an important problem in many practical applications. This problem is often referred to as supervised concept learning, and has been shown to be relevant in e.g. READ MORE

  5. 3. Perspectives on Probabilistic Graphical Models

    Author : Dong Liu; Ragnar Thobaben; Harri Lähdesmäki; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Bayesian methods; graphical models; inference; learning; statistics; Electrical Engineering; Elektro- och systemteknik;

    Abstract : Probabilistic graphical models provide a natural framework for the representation of complex systems and offer straightforward abstraction for the interactions within the systems. Reasoning with help of probabilistic graphical models allows us to answer inference queries with uncertainty following the framework of probability theory. READ MORE

  6. 4. Towards Guidelines for Conducting Software Process Simulation in Industry

    Author : Nauman bin Ali; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES;

    Abstract : Background: Since the 1950s explicit software process models have been used for planning, executing and controlling software development activities. To overcome the limitation of static models at capturing the inherent dynamism in software development, Software Process Simulation Modelling (SPSM) was introduced in the late 1970s. READ MORE

  7. 5. Risk stratification in cardiac surgery: Algorithms and applications

    Author : Johan Nilsson; Thoraxkirurgi; []
    Keywords : MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Surgery; orthopaedics; traumatology; Kardiovaskulära systemet; Cardiovascular system; Cardiac surgery; Statistics; Artificial neural networks; Resource utilization; Mortality; Risk factors; Kirurgi; ortopedi; traumatologi;

    Abstract : The aims of this research was to compare different risk score algorithms with regard to their validity to predict 30-day and one-year mortality after open-heart surgery, to evaluate if the preoperative risk stratification model EuroSCORE predicts the different components of resource utilization in cardiac surgery, and to systematically evaluate the accuracy and performance of artificial neural networks (ANNs) to select and rank the most important risk factors for operative mortality in open-heart surgery. Preoperative evaluation of the surgical risk is an important component in cardiac surgery. READ MORE