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Similarly, Yordanova et al [60] used RF algorithms to detect social behavior from transcripts of daily conversations.
We provide information on the experimental setting by describing the (1) machine learning runs (R, when reported with run number), (2) repeated cross-validation routine, (3) recursive feature elimination (RFE) algorithm, (4) hyperparameters in the cross-validation, and (5) the evaluation metrics of the machine learning models.
JMIR Aging 2022;5(1):e28333
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Yordanova et al [24] were the first to investigate the applicability of NLP and machine learning methodologies on data from a naturalistic observation study by Demiray et al [6]; they introduced an NLP pipeline and machine learning routines to automatically code the social behaviors and interactions (eg, talking to a partner or daughter/son, giving advice, receive support, etc) in the transcripts of recorded conversations.
J Med Internet Res 2020;22(9):e19133
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