New Data from Massachusetts General Hospital Illuminate Findings in Machine Lear ning (Toward Generalizable Machine Learning Models In Speech, Language, and Hear ing Sciences : Estimating Sample Size and Reducing Overfitting)
New Data from Massachusetts General Hospital Illuminate Findings in Machine Lear ning (Toward Generalizable Machine Learning Models In Speech, Language, and Hear ing Sciences : Estimating Sample Size and Reducing Overfitting)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from Boston, Ma ssachusetts, by NewsRx correspondents, research stated, “Many studies using mach ine learning (ML) in speech, language, and hearing sciences rely upon cross -val idations with single data splitting. This study’s first purpose is to provide qu antitative evidence that would incentivize researchers to instead use the more r obust data splitting method of nested k fold cross -validation.” Financial support for this research came from NIH National Institute on Deafness & Other Communication Disorders (NIDCD).
Key words
Boston/Massachusetts/United States/No rth and Central America/Cyborgs/Emerging Technologies/Machine Learning/Massa chusetts General Hospital
NETL
NSTL