Improving Clustering Results through Active Learning

<p dir="ltr">Data labelling is a task that arises in various fields, including image processing, voice recognition, and text classification. Active Learning (AL) is a method that can be used to simplify this task. This study focuses on tabular data and the classification of disabilities. We use the English Longitudinal Study of Ageing (ELSA) and different socio-demographic, disease, and disability factors to group participants into various disability levels. Since the ground truth is unknown, we employ different clustering methods. The results show that by combining AL strategies, even with small amounts of data, we can achieve accuracy comparable to that of the entire dataset.</p>