Sökning: "Interpretable Machine Learning"

Visar resultat 11 - 15 av 23 avhandlingar innehållade orden Interpretable Machine Learning.

  1. 11. Applications of Unsupervised Deep Learning for Analysing Time-Varying Power Quality Big Data

    Författare :Roger Alves de Oliveira; Math Bollen; Sarah Rönnberg; Matti Lehtonen; Luleå tekniska universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; power quality; power system harmonics; electric power distribution; interharmonics; big data analytics; pattern analysis; unsupervised learning; deep learning; artificial intelligence; geomagnetically induced currents; Electric Power Engineering; Elkraftteknik;

    Sammanfattning : Continuous power quality monitoring allows grid stakeholders to obtain information about the performance of the network and costumer facilities. Moreover, the analysis of continuous monitoring allows researchers to obtain knowledge on power quality phenomena. Power quality measurements result in a large amount of data. LÄS MER

  3. 12. Aggregation as Unsupervised Learning in Software Engineering and Beyond

    Författare :Maria Ulan; Welf Löwe; Neil Ernst; Linnéuniversitetet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; quality assessment; quantitative methods; aggregation; multi-criteria decision making; unsupervised machine learning; Data- och informationsvetenskap; Computer and Information Sciences Computer Science;

    Sammanfattning : Ranking alternatives is fundamental to effective decision making. However, creating an overall ranking is difficult if there are multiple criteria, and no single alternative performs best across all criteria. Software engineering is no exception. LÄS MER

  4. 13. Uncovering biomarkers and molecular heterogeneity of complex diseases : Utilizing the power of Data Science

    Författare :Sara Younes; Linda Holmfeldt; Jan Komoroski; Aedin Culhane; Uppsala universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Complex Disease; Cancer; Autoimmune diseases; Acute Myeloid Leukemia; Systemic Lupus Erythematosus; Bioinformatics; Machine Learning; Data Science; Statistical Analysis; Bioinformatics; Bioinformatik; Computer Science; Datavetenskap;

    Sammanfattning : Uncovering causal drivers of complex diseases is yet a difficult challenge. Unlike single-gene disorders complex diseases are heterogeneous and are caused by a combination of genetic, environmental, and lifestyle factors which complicates the identification of patient subgroups and the disease causal drivers. LÄS MER

  5. 14. Trustworthy explanations : Improved decision support through well-calibrated uncertainty quantification

    Författare :Helena Löfström; Ulf Seigerroth; Ulf Johansson; Patrick Mikalef; Jönköping University; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Explainable Artificial Intelligence; Interpretable Machine Learning; Decision Support Systems; Uncertainty Estimation; Explanation Methods;

    Sammanfattning : The use of Artificial Intelligence (AI) has transformed fields like disease diagnosis and defence. Utilising sophisticated Machine Learning (ML) models, AI predicts future events based on historical data, introducing complexity that challenges understanding and decision-making. LÄS MER

  7. 15. User Modeling for Adaptive Virtual Reality Experiences : Personalization from Behavioral and Physiological Time Series

    Författare :Luis Quintero; Uno Fors; Lijffijt Jefrey; Stockholms universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; virtual reality; VR; machine learning; ML; user modeling; personalization; wearable; heart rate; HRV; biosensors; movement; behavioral; user experience; UX; spatial computing; metaverse; extended reality; XR; data- och systemvetenskap; Computer and Systems Sciences;

    Sammanfattning : Research in human-computer interaction (HCI) has focused on designing technological systems that serve a beneficial purpose, offer intuitive interfaces, and adapt to a person's expectations, goals, and abilities. Nearly all digital services available in our daily lives have personalization capabilities, mainly due to the ubiquity of mobile devices and the progress that has been made in machine learning (ML) algorithms. LÄS MER