Measuring the Severity of the Signs of Eating Disorders Using Machine Learning Techniques

Prasanna, S.Gulati, A.Karmakar, S.Hiranmayi, M.Y.Anand Kumar, M.2026-02-062024CEUR Workshop Proceedings, 2024, Vol.3740, , p. 881-88716130073https://doi.org/https://idr.nitk.ac.in/handle/123456789/28984The paper presents the results submitted by Team SCaLAR-NITK for task 3 of eRisk Lab at CLEF 2024 [1]. The dataset provided by the task organizers consisted of 74 subjects for training and 18 for testing. We begin by describing the data cleaning and preprocessing steps. Subsequently, we outline various approaches used to address the problem, such as Word2Vec, TF-IDF, Backtranslation and Dimensionality Reduction, among others. Finally, we summarize the results obtained from each approach. Our solutions demonstrated strong performance, achieving the best results in 7 out of the 8 evaluated metrics. Â© 2024 Copyright for this paper by its authors.BacktranslationMachine LearningTF-IDFWord2VecMeasuring the Severity of the Signs of Eating Disorders Using Machine Learning Techniques