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Showing result 1 - 5 of 884 swedish dissertations matching the above criteria.

2. 1. Order in the random forest

   Author : Isak Karlsson; Henrik Boström; Lars Asker; Pierre Geurts; Stockholms universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine learning; random forest; ensemble; time series; data series; sequential data; sparse data; high-dimensional data; Computer and Systems Sciences; data- och systemvetenskap;

   Abstract : In many domains, repeated measurements are systematically collected to obtain the characteristics of objects or situations that evolve over time or other logical orderings. Although the classification of such data series shares many similarities with traditional multidimensional classification, inducing accurate machine learning models using traditional algorithms are typically infeasible since the order of the values must be considered. READ MORE

4. 2. Learning from Complex Medical Data Sources

   Author : Jonathan Rebane; Panagiotis Papapetrou; Isak Samsten; Myra Spiliopoulou; Stockholms universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Data Science; Healthcare; Complex Data; Explainable AI; Deep Learning; data- och systemvetenskap; Computer and Systems Sciences;

   Abstract : Large, varied, and time-evolving data sources can be observed across many domains and present a unique challenge for classification problems, in which traditional machine learning approaches must be adapted to accommodate for the complex nature of such data. Across most domains, there is also a need for machine learning models that are both well-performing and interpretable, to help provide explanations of a model's decisions that stakeholders can trust and take appropriate actions with. READ MORE

5. 3. Learning predictive models from graph data using pattern mining

   Author : Thashmee M. Karunaratne; Henrik Boström; Lars Asker; Nada Lavraˇc; Stockholms universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Graph Data; Pattern Mining; Classification; Regression; Predictive Models; Computer and Systems Sciences; data- och systemvetenskap;

   Abstract : Learning from graphs has become a popular research area due to the ubiquity of graph data representing web pages, molecules, social networks, protein interaction networks etc. However, standard graph learning approaches are often challenged by the computational cost involved in the learning process, due to the richness of the representation. READ MORE

6. 4. Image Based Visualization Methods for Meteorological Data

   Author : Björn Olsson; Anders Ynnerman; Reiner Lenz; Anders Hast; Linköpings universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Visualization; Meteorological Data; Artificial Neural Networks; High-Dynamic-Range images; Satellite Data; Classification; Computer science; Datavetenskap;

   Abstract : Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. READ MORE

7. 5. Data-driven decision support in digital retailing

   Author : Dirar Sweidan; Ulf Johansson; Beatrice Alenljung; Anders Gidenstam; Högskolan i Skövde; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Digital Retailing; Decision Support; Probabilistic Prediction; Calibration; Product Returns; Customer Churn; Binary Classification; Scikit-Learn;

   Abstract : In the digital era and advent of artificial intelligence, digital retailing has emerged as a notable shift in commerce. It empowers e-tailers with data-driven insights and predictive models to navigate a variety of challenges, driving informed decision-making and strategic formulation. READ MORE