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Influence of Interactive Visualizations on Students' Learning Experience in Machine Learning

Renţea, Ilinca (author)

With the fast integration of Machine Learning(ML) into several industries, the motivation to develop effective pedagogical strategies for teaching this complex and evolving field has become critical. Machine Learning, once mainly a topic in Computer Science Bachelor programs, is now widely integrated into various majors and introduced at earlier...

master thesis 2024

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Bayesian Sensitivity Analysis for a Missing Data Model: Incorporating Covariates via a Cox Model

van Vliet, Christian (author)

In problems with missing data, the data are often considered to be missing at random. This assumption can not be checked from the data. We need to assess the sensitivity of study conclusions to violations of non-identifiable assumptions. This thesis performs Bayesian sensitivity analysis for a missing data model with life time outcomes and...

master thesis 2023

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The influence of the dimensionality on the parameters of the learning curve model

Mereuta, Andrei (author)

Learning curves in machine learning are graphical representations that depict the relationship between a model's performance and the amount of training data it has been exposed to. They play a fundamental role in obtaining the knowledge and skills across a range of domains. Although there are already quite some researches studying machine...

bachelor thesis 2023

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How Well do Clustering Similarities-Based Concept Drift Detectors Identify Drift in case of Synthetic/Real-World Data?

Pohl, Jindřich (author)

Concept drift is an unforeseeable change in the underlying data distribution of streaming data, and because of such a change, deployed classifiers over that data show a drop in accuracy. Concept drift detectors are algorithms capable of detecting such a drift, and unsupervised ones detect drift without needing the data’s actual labels, which can...

bachelor thesis 2023

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Evaluating Data Distribution Based Concept Drift Detectors

Kanniainen, Konsta (author)

Various techniques have been studied to handle unexpected changes in data streams, a phenomenon called concept drift. When the incoming data is not labeled and the labels are also not obtainable with a reasonable effort, detecting these drifts becomes less trivial. This study evaluates how well two data distribution based label-independent drift...

bachelor thesis 2023

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Detecting Concept Drift in Deployed Machine Learning Models: How well do Margin Density-based concept drift detectors identify concept drift in case of synthetic/real-world data?

André, Baptiste (author)

When deployed in production, machine learning models sometimes lose accuracy over time due to a change in the distribution of the incoming data, which results in the model not reflecting reality any longer. A concept drift is this loss of accuracy over time. Drift detectors are algorithms used to detect such drifts. Drift detectors are important...

bachelor thesis 2023

document

A Comparative Study of Process Mining Tools: FlexFringe, ProM, MINT and PRINS

Kloppenburg, Mayke (author)

Nowadays, software is an integral part of many companies. However, the codebase can grow large and complicated and is often insufficiently documented. To gain insight, tools have been made to infer state machines and process models from software logs. These tools produce different types of models such as automata and Petri nets. The main...

master thesis 2022

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Deep learning-based surrogate modelling for 2D flood simulation

Stolp, Thomas (author)

Flood simulations can give insight into the consequences of flood scenario's and can help to create hazard- and risk maps to support decision-making in flood risk management and in crisis management. 2D hydrodynamic simulations give accurate descriptions of the propagation of a flood and rely on advanced numerical methods to solve a set of...

master thesis 2021

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Measuring the quality of publicly available synthetic IDS datasets: A comparative study

Brussen, Arjen (author)

Year after year, the amount of network intrusions and costs associated to them rises. Research in this area is, therefore, of high importance and provides valuable insight in how to prevent or counteract intrusions. Machine learning algorithms seem to be a promising answer for automated network intrusion detection, as their results often reach...

master thesis 2021

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Learning the Limit Order Book: a comprehensive mix between stochastic and machine learning models for generation and prediction

Özyar, Muhammed Imran (author)

The field of finance is an interesting field in which much research takes place. In particular, its sub-field of modeling the dynamics of order books is an interesting field, since it translates into modeling the behaviour of traders on the market. Most of the models proposed in this field can be divided into stochastic models or machine...

master thesis 2021

document

Prediction models for adverse outcomes in Covid-19 patients

Smit, Jim (author)

Background: The covid-19 pandemic has overwhelmed hospitals worldwide and clinical prediction models may assist in timely identification of covid-19 patients at risk for clinical deterioration, i.e. `early warning'. In this article, we report on the development and validation of a new early warning model that predicts unplanned ICU admission or...

master thesis 2021

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Influence of shared information on predictability in human-agent teams

Nagy, Timea (author)

Understanding trust in human-agent teams is of utmost importance if we want to ensure an efficient and effective collaboration. It is well known that predictability is a core component of trust, however it is still unclear what kind of information an agent should share in order to be perceived as predictable. Here we show that in a simple world...

bachelor thesis 2021

document

Assessing the Suitability of Panako for Music Identification in Movies

Nair, Ruben (author)

Audio fingerprinting is a technique that allows for fast identification of music. Research concerning this technique first emerged around the 2000s and has lead to several applications, like Shazam. More recently, developments in this area have slowed down, even though there are still new challenges emerging. This paper investigates one of these...

bachelor thesis 2021

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Analysing the performance of the OLAF framework in the context of identifying music in movies

Hildebrand, Casper (author)

This paper presents the findings of a benchmark performed on the audio fingerprinting framework OLAF in the context of movie music. The goal is to find a music identification framework suitable for automatically identifying a song from a movie clip. This research aims to find how well OLAF performs in this context with regard to the criteria...

bachelor thesis 2021

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Performance of the Dejavu audio fingerprinting framework in music identification in movies

Struharová, Natália (author)

Audio fingerprinting is one of the standard solutions for music identification. The underlying technique is designed to be robust to signal degradation such that music can be identified despite its presence. One of the newly emerged applications of a possibly challenging nature is music identification in movies. This paper examines the audio...

bachelor thesis 2021

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Directability’s influence on human-agent trust

Jiang, Yuxin (author)

Mutual human-agent trust is of great importance for humans and agents to complete a task collaboratively. This paper aims at studying one of the factors influencing this mutual trust, the directability of humans to agents. Previous studies either take directability as a general concept without looking<br/>into its different representations or...

bachelor thesis 2021

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Sharing human mental model with an AI agent to achieve team effectiveness

Ziad Ahmad Saad Soliman Nawar, Ziad (author)

The collaboration between AI agents (Artificial Intelligence) and human is an essential part of achieving complex goals more efficiently. Many aspects are influential in achieving effective teamwork. One of them is trust. In addition, sharing the mental model would improve the understanding of the other’s behavior and the prediction of their...

bachelor thesis 2021

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Evaluating the Suitability of SoundFingerprinting for Music Identification in Movies

Huisman, Tim (author)

Audio fingerprinting has shown to be an effective approach to music identification, having properties robust to noise and signal degradations. A field in which audio fingerprinting has not been evaluated yet is music identification in movies. In movies, music is often accompanied with background noise, sound effects and dialogue, and further...

bachelor thesis 2021

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Indexing Music in Movies Using Audio Fingerprinting: An Audioneex Study

Wever, Cas (author)

Music indexing, the practice of identifying songs contained in an audio sample, is an approach that is widely used. As an underlying technique, "audio fingerprinting" can be used. In this technique, an audio sample is converted to a fingerprint; a smaller representation of the audio. This fingerprint is compared to a database of fingerprinted...

bachelor thesis 2021

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The Influence of Information Sharing on the Predictability of the Human to an Agent

van der Kruk, Stephen (author)

Mutual predictability shows itself as a contributing factor to mutual trust and is known to improve the effectiveness in a human-agent teamwork setting. As team members communicate to coordinate the team through the task, the question arises as to what information the human should share to be predictable to an agent. To experiment with measuring...

bachelor thesis 2021