Data preprocessing is crucial in the Machine Learning pipeline because the models'
learning ability directly affects the quality of data and the underlying information acquired …

In the evolving field of solar energy, precise forecasting of Solar Irradiance (SI) stands as a
pivotal challenge for the optimization of photovoltaic (PV) systems. Addressing the …

In this study we use machine learning to perform explainable business sector prediction
from financial statements. Financial statements are a valuable source of information on the …

Incomplete data is a crucial challenge to data exploration, analytics, and visualization
recommendation. Incomplete data would distort the analysis and reduce the benefits of any …

This paper presents a vulnerable road user (VRU) tracking algorithm capable of handling
noisy and missing detections from heterogeneous sensors. We propose a cooperative …

Imputation allows datasets to be used with algorithms that cannot handle missing values by
themselves. However, missing values may in principle contribute useful information that is …

Creating successful projects is challenging and estimation of software development efforts is
thus an important activity of the software engineering community. It enables project …

Abstract Background/Objectives: The Internet of Things (IoT) relies on consistent data
delivery, crucial for maintaining service quality. However, challenges like connection issues …

This thesis explores the pivotal role of capabilities and technologies in the digital
transformation of the banking sector, with a focus on identifying optimal strategies within …

This thesis is part of an extensive collaboration between the Dutch Ministry of Infrastructure
and Water Management (I&W) and Leiden University. My first personal encounter with I&W …