
Be the first to like this
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.
Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.
Published on
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.
Clipping is a handy way to collect and organize the most important slides from a presentation. You can keep your great finds in clipboards organized around topics.
Be the first to comment