  Vocal disorders have affected several patients all over the world. Due to the
inherent difficulty of diagnosing vocal disorders without sophisticated
equipment and trained personnel, a number of patients remain undiagnosed. To
alleviate the monetary cost of diagnosis, there has been a recent growth in the
use of data analysis to accurately detect and diagnose individuals for a
fraction of the cost. We propose a cheap, efficient and accurate model to
diagnose whether a patient suffers from one of three vocal disorders on the
FEMH 2018 challenge.
