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In recent years, applications of data mining method
s are become more popular in many fields of medical
diagnosis and evaluations. The data mining methods
are appropriate tools for discovering and extractin
g
of available knowledge in medical databases. In thi
s study, we divided 11 data mining algorithms into
five
groups which are applied to a dataset of patient’s
clinical variables data with Parkinson’s Disease (P
D) to
study the disease progression. The dataset includes
22 properties of 42 people that all of our algorit
hms
are applied to this dataset. The Decision Table wit
h 0.9985 correlation coefficients has the best accu
racy
and Decision Stump with 0.7919 correlation coeffici
ents has the lowest accuracy.
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