Classification Techniques in Machine Learning: Applications and Issues Pages 459-465

Classification Techniques in Machine Learning: Applications and Issues
Pages 459-465Creative Commons License

Aized Amin Soofi and Arshad Awan
DOI: https://doi.org/10.6000/1927-5129.2017.13.76

Published: 29 August 2017

Abstract: Classification is a data mining (machine learning) technique used to predict group membership for data instances. There are several classification techniques that can be used for classification purpose. In this paper, we present the basic classification techniques. Later we discuss some major types of classification method including Bayesian networks, decision tree induction, k-nearest neighbor classifier and Support Vector Machines (SVM) with their strengths, weaknesses, potential applications and issues with their available solution. The goal of this study is to provide a comprehensive review of different classification techniques in machine learning. This work will be helpful for both academia and new comers in the field of machine learning to further strengthen the basis of classification methods.

Keywords: Machine learning, classification, classification review, classification applications, classification algorithms, classification issues.