Different Types of Multi Class Classification Algorithms: A Study

Authors

  • Johnsymol J Dept. of Computer Application, Saintgits College of Applied Sciences, M G University, Kerala, India
  • Krishnan R Dept. of Computer Application, Saintgits College of Applied Sciences, M G University, Kerala, India
  • Ziyad Nazeer Dept. of Computer Application, Saintgits College of Applied Sciences, M G University, Kerala, India

DOI:

https://doi.org/10.26438/ijcse/v9i3.4144

Keywords:

Classification, Decision tree, Naive Baye, SVM

Abstract

Classification is a crucial aspect of machine learning. Multi class Classification has an important role in the classification. It is an on-going research in machine leaning field. In this paper we will come to know about multi class classification algorithms. We will see different algorithms like Decision Tree, SVM, Random Forest, Naive Bayes etc. This is clear cut representation of the basic advantages and limitations regarding different types of classification algorithms and the various measures for implementing results. Nowadays, these types of algorithms are playing a substantial role among different program sequences so as to improve the quality of classification.

References

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Published

2021-03-31
CITATION
DOI: 10.26438/ijcse/v9i3.4144
Published: 2021-03-31

How to Cite

[1]
J. Johnsymol, R. Krishnan, and Z. Nazeer, “Different Types of Multi Class Classification Algorithms: A Study”, Int. J. Comp. Sci. Eng., vol. 9, no. 3, pp. 41–44, Mar. 2021.

Issue

Vol. 9 No. 3 (2021): IJCSE March Edition

Section

Survey Article

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