Search for dissertations about: "Supervised Machine Learning"

Showing result 1 - 5 of 87 swedish dissertations containing the words Supervised Machine 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. Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things : Enhancing COVID-19 & Early Sepsis Detection

    Author : Mahbub Ul Alam; Rahim Rahmani; Jaakko Hollmén; Sadok Ben Yahia; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Internet of Medical Things; Patient-Centric Healthcare; Clinical Decision Support System; Predictive Modeling in Healthcare; Health Informatics; Healthcare analytics; COVID-19; Sepsis; COVID-19 Detection; Early Sepsis Detection; Lung Segmentation Detection; Medical Data Annotation Scarcity; Medical Data Sparsity; Medical Data Heterogeneity; Medical Data Security Privacy; Practical Usability Enhancement; Low-End Device Adaptability; Medical Significance; Interpretability; Visualization; LIME; SHAP; Grad-CAM; LRP; Electronic Health Records; Thermal Image; Tabular Medical Data; Chest X-ray; Machine Learning; Deep Learning; Federated Learning; Semi-Supervised Machine Learning; Multi-Task Learning; Transfer Learning; Multi-Modality; Natural Language Processing; ClinicalBERT; GAN; data- och systemvetenskap; Computer and Systems Sciences;

    Abstract : This thesis presents a critical examination of the positive impact of Machine Learning (ML) and the Internet of Medical Things (IoMT) for advancing the Clinical Decision Support System (CDSS) in the context of COVID-19 and early sepsis detection.It emphasizes the transition towards patient-centric healthcare systems, which necessitate personalized and participatory care—a transition that could be facilitated by these emerging fields. READ MORE

  5. 3. Machine Learning for Wireless Link Adaptation : Supervised and Reinforcement Learning Theory and Algorithms

    Author : Vidit Saxena; Joakim Jaldén; Mats Bengtsson; Hugo Tullberg; Jakob Hoydis; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Wireless Communications; Reinforcement Learning; Multi-Armed Bandits; Thompson Sampling; Convex Optimization; Deep Learning; Electrical Engineering; Elektro- och systemteknik;

    Abstract : Wireless data communication is a complex phenomenon. Wireless links encounter random, time-varying, channel effects that are challenging to predict and compensate. Hence, to optimally utilize the channel, wireless links adapt the data transmission parameters in real time. READ MORE

  6. 4. 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

  7. 5. Automated Malware Detection and Classification Using Supervised Learning

    Author : Raja Muhammad Khurram Shahzad; Niklas Lavesson; Martin Boldt; Welf Löwe; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Malware Detection; Android Malware; Machine Learning; Static Malware Analysis; Cyber Security; Ensemble learning; Supervised Learning; Feature Selection; Computer Science; Datavetenskap;

    Abstract : Malware has been one of the key concerns for Information Technology security researchers for decades. Every year, anti-malware companies release alarming statistics suggesting a continuous increase in the number and types of malware. READ MORE