An In-Depth Comparative Analysis of Machine Learning Techniques for Addressing Class Imbalance in Mental Health Prediction

Tsholofelo Mokheleli, Tebogo Bokaba, Tinofirei Museba

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The application of machine learning (ML) in predicting mental healthcare faces a challenge due to imbalanced datasets. ML techniques analyse extensive datasets to make predictions; however, the unequal distribution of samples, with the majority belonging to diagnosed mental disorders, can lead to biased model training and limited generalisation. To mitigate the issue of class imbalance in mental health datasets, this study employed diverse ML techniques, namely, resampling, ensemble, and algorithm-specific approaches and metrics such as accuracy, precision, recall and F1 score. The dataset used was collected from the Open Sourcing Mental Illness website, spanning 2016 to 2021. The findings indicate that ensemble techniques, particularly Random Forest, excelled in managing class imbalance compared to other methods. Beyond conventional performance metrics, the study introduced Kappa, balanced accuracy, and geometric mean to evaluate model effectiveness. These findings provide valuable insights for improving mental health predictions, enabling early diagnosis and personalised treatment strategies.

Original languageEnglish
Title of host publicationInternational Conference on Information Systems, ICIS 2023
Subtitle of host publication"Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies"
PublisherAssociation for Information Systems
ISBN (Electronic)9781713893622
Publication statusPublished - 2023
Event44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023 - Hyderibad, India
Duration: 10 Dec 202313 Dec 2023

Publication series

NameInternational Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies"

Conference

Conference44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023
Country/TerritoryIndia
CityHyderibad
Period10/12/2313/12/23

Keywords

  • Class imbalance
  • Cross-validation
  • Machine learning
  • Mental health prediction
  • Resampling methods

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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