Classification Techniques in Machine Learning

Applications and Issues

Authors

  • Aized Amin Soofi Allama Iqbal Open University, Islamabad, Pakistan
  • Arshad Awan Allama Iqbal Open University, Islamabad, Pakistan

Keywords:

Machine learning, classification, classification review, classification applications, classification algorithms, classification issues

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.

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Published

2017-01-05

How to Cite

Aized Amin Soofi, & Arshad Awan. (2017). Classification Techniques in Machine Learning: Applications and Issues. Journal of Basic & Applied Sciences, 13, 459–465. Retrieved from https://setpublisher.com/index.php/jbas/article/view/1715

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Section

Computer Sciences