Increasing the Accuracy of Brain Stroke Classification using Random Forest Algorithm with Mutual Information Feature Selection

Increasing the Accuracy of Brain Stroke Classification using Random Forest Algorithm with Mutual Information Feature Selection

Brain stroke stands out as a leading cause of death, distinguishing it from common illnesses and highlighting the critical need to utilize machine learning techniques to identify symptoms. Among these techniques, the Random Forest (RF) algorithm emerged as the main candidate because of its optimal a...

Full description

Saved in:
Bibliographic Details
Main Authors: Fachruddin Fachruddin, Errissya Rasywir, Yovi Pratama
Format: Article
Language:English
Published: Ikatan Ahli Informatika Indonesia 2024-08-01
Series:Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Subjects:
random forest
strokes
brain
mutual information
features
Online Access:https://jurnal.iaii.or.id/index.php/RESTI/article/view/5795
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items