Different types of Bayesian networks may be used
for supervised classification. We combine such approaches
together with feature selection and discretization and we show
that such combination gives rise to powerful classifiers. A large
choice of data sets from the UCI machine learning repository
are used in our experiments and an application to Epilepsy type
prediction based on PET scan data confirms the efficiency of
our approach.

العنوان

15th IEEE International Conference on Machine Learning and Applications (ICMLA)

الناشر

IEEE

بلد الناشر

الولايات المتحدة الأمريكية

Indexing

Scopus

معامل التأثير

None

نوع المنشور

Both (Printed and Online)

المجلد

--

السنة

--

الصفحات

--