Open AccessComprehensive study on ensemble classification for medical applications
Author(s) -
Rosaida Rosly,
Mokhairi Makhtar,
Mohd Khalid Awang,
Mohd Isha Awang,
Mohd Nordin Abdul Rahman,
Hairulnizam Mahdin
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.14.12822
Subject(s) - computer science , data mining , ensemble learning , class (philosophy) , machine learning , artificial intelligence , statistical classification , data science
The aims of this paper were to provide a comprehensive review of classification techniques and their alternative approaches in data mining. Classification is a data mining technique that assigns categories to a collection of data to aide in more accurate predictions and analyses. It is one of the several methods intended to make the analysis of very large datasets effective. The goal of classification is to accurately predict the target class for each case in the data. One of the classification approaches is the ensemble method. In recent years, the usage of ensemble method in medical application has been increasing. Not only in medical areas, it can also help researchers to solve modem problems in many fields like machine learning, data mining and other related areas.