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Ramsundersingh, Pravesha (author)
A learning curve can serve as an indicator of the “performance of trained models versus the training set size” [1]. Recent research on learning curve analysis has been carried out within the Learning Curve Database (LCDB) [2] This paper will investigate if there are similarities amongst these curves by clustering those provided by the LCDB. The...
bachelor thesis 2024
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Johari, Pratham (author)
This study explores the extrapolation of learning curves, a crucial aspect in evaluating learner performance with varying dataset sample sizes. We use the Learning Curve Prior Fitted Network (LC-PFN), a transformer pre-trained on synthetic data with proficiency in approximate Bayesian inference, to investigate its predictive accuracy using the...
bachelor thesis 2024
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Wigmans, Bram (author)
This paper examines whether complex high-dimensional data that describes the dynamics of a cantilever beam can be transformed into a less complex system. In particular, the transformation that is examined is the reduction of the dimension. An essential aspect of this study involves the implementation of a linear autoencoder, which is a type of...
bachelor thesis 2023
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Holtgrefe, Tim (author)
Microtubules are long cylindrical polymers, assembled from tubulin proteins. Microtubule ends can be visualized using fluorescence and confocal microscopy. This allows for the study of microtubule dynamics. However, the manual annotation of microtubules is laborious, which is why automated tracking methods are used. In this project we have...
bachelor thesis 2023
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Trinh, Eames (author)
Federated learning enables training machine learning models on decentralized data sources without centrally aggregating sensitive information. Continual learning, on the other hand, focuses on learning and adapting to new tasks over time while avoiding the catastrophic forgetting of knowledge from previously encountered tasks. Federated...
bachelor thesis 2023
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Persianov, Petr (author)
Celiac disease is a genetic autoimmune disorder caused by a negative reaction to gluten associated with alterations in the gut microbiome. This study explored the potential of machine learning models and feature selection methods in identifying biomarkers for celiac disease using gut microbiome data. The performance of several machine learning...
bachelor thesis 2023
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Das, Aratrika (author)
Type 2 Diabetes is a very prevalent disease in current times and leads to significant adverse effects. Recently, there has been a growing interest in the association of the human gut microbiome with respect to chronic diseases like Type 2 Diabetes with the aim to identify biomarkers. In this study, we researched the effect of different machine...
bachelor thesis 2023
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Gogora, Kristián (author)
Nonconvexity in learning curves is almost always undesirable. A machine learning model with a non-convex learning curve either requires a larger quantity of data to observe progress in its accuracy or experiences an exponential decrease of accuracy at low sample sizes, with no improvement in accuracy even when more data points are added. This...
bachelor thesis 2023
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Jongejans, Liselotte (author)
This research paper aims to investigate the adequacy of concepts taught during an introductory machine learning course in preparing students for subsequent courses and their professional careers. The study adopts a comprehensive approach, including a literature review, interviews with teaching staff of follow-up courses, and a survey...
bachelor thesis 2023
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Kalandadze, Anna (author)
Learning curves display predictions of the chosen model’s performance for different training set sizes. They can help estimate the amount of data required to achieve a minimal error rate, thus aiding in reducing the cost of data collection. However, our understanding and knowledge of the various shapes of learning curves and their applicability...
bachelor thesis 2023
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Andrasz, Aleksandra (author)
Depression diagnosis and treatment remain difficult tasks that could be improved with machine learning models. But those automatic systems should be reliable to apply in clinical psychology settings. Performing predictions in this field is most commonly done using supervised learning models, which rely on well-established annotations. Therefore...
bachelor thesis 2023
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Vincenti, Jort (author)
To validate the results of a medical trial, there must be an overlap between the treatment and control groups. This implies the crucial need for good evaluation methods. This study, therefore, aimed to evaluate the overlap between causal classes using the Nearest Neighbours’ methods. Firstly, a case study was built around the common failures of...
bachelor thesis 2023
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Buşe, Florena (author)
Thus far the democratization of machine learning, which resulted in the field of AutoML, has focused on the automation of model selection and hyperparameter optimization. Nevertheless, the need for high-quality databases to increase performance has sparked interest in correlation-based feature selection, a simple and fast, yet effective approach...
bachelor thesis 2023
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Butenaerts, Mathieu (author)
Because of the growing presence of artificial intelligence, developers are looking for more efficient methods to construct machine learning algorithms. Program synthesizers allow us to produce algorithms consisting of scalers, feature selection and classifiers. Each of these pipelines is a potential solution to the given machine learning task....
bachelor thesis 2023
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Sihlovec, Oliver (author)
Scientific problems are often concerned with optimization of control variables of complex systems, for instance hyperparameters of machine learning models. A popular solution for such intractable environments is Bayesian optimization. However, many implementations disregard dynamic evaluation costs associated with the optimization procedure....
bachelor thesis 2023
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Gökçe, Tolga (author)
An algal bloom is defined as a rapid increase in common algae (phytoplankton) abundance in water bodies and it can occur when a group of certain environmental factors is combined. If the algae populations grow out of control, such algal blooms become problematic and cause damage to the ecosystem, such phenomena are called harmful algal blooms....
bachelor thesis 2023
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Kirchner, Joris (author)
Neural network is an active research field which involves many different (unsolved) issues, for example, different types of configuration of the network architectures, training strategies, etc. Amongst these active issues, the choice of loss (or cost) functions plays an important role in how a neural network model is to be optimized (trained)...
bachelor thesis 2022
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Geerts, Nathan (author)
In this report, a transformer based deep learning proton dose calculation algorithm called Dose Transformer Algorithm (DoTA) is described. This model learns to predict proton dose distributions by being trained with Monte Carlo generated data. Monte Carlo is the golden standard of proton dose calculation because it is very accurate, but it has...
bachelor thesis 2022
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van den Belt, Glenn (author)
Earthquakes can have tremendous effects. They can result in casualties, massive damage, and hurt the economy. Therefore, one would like to predict earthquakes as early as possible and with the highest accuracy possible. This paper contains the proposal for the optimal prediction-time, which is the time between the execution of a prediction and...
bachelor thesis 2022
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Dijkstra, Finn (author)
Packages to encode Machine Learned models into optimization problems is an underdeveloped area, despite the advantages is could provide. The main draw of implementing Machine Learned models into optimization models, is that it allows the optimizer to better account for the human experience.<br/>Maragno D., Wiberg H. et al. constructed an...
bachelor thesis 2022
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