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Analyzing the Effect of Data Impurity on the Detection Performances of Mental Disorders. (arXiv:2308.05133v1 [q-bio.NC])
cs.LG updates on arXiv.org arxiv.org
The primary method for identifying mental disorders automatically has
traditionally involved using binary classifiers. These classifiers are trained
using behavioral data obtained from an interview setup. In this training
process, data from individuals with the specific disorder under consideration
are categorized as the positive class, while data from all other participants
constitute the negative class. In practice, it is widely recognized that
certain mental disorders share similar symptoms, causing the collected
behavioral data to encompass a variety of attributes associated …
arxiv behavioral data binary bio classifiers data detection interview positive process setup training