Toward Generalizable Machine Learning Models in Speech, Language, and Hearing Sciences: Estimating Sample Size and Reducing Overfitting.

Purpose: Many studies using machine learning (ML) in speech, language, and hearing sciences rely upon cross-validations with single data splitting. This study's first purpose is to provide quantitative evidence that would incentivize researchers to instead use the more robust data splitting method o...

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Publicado en:	Journal of Speech, Language & Hearing Research Vol. 67; no. 3; pp. 753 - 782
Autores principales:	Ghasemzadeh, Hamzeh, Hillman, Robert E., Mehta, Daryush D.
Formato:	Artículo
Publicado:	American Speech-Language-Hearing Association Mar2024
Materias:	Language & languages Computer simulation Speech Quantitative research Hearing Allied health education Speech therapy education Sample size (Statistics) Probability theory Descriptive statistics System analysis Machine learning Comparative studies
Acceso en línea:	Ver este registro en EBSCOhost