Comprehensive review of supervised machine learning algorithms to identify the best and error free
Department of Computer Sc. Michael Okpara University of Agriculture, Umudike, Nigeria.
Review
International Journal of Scholarly Research in Engineering and Technology, 2023, 02(01), 013-019.
Article DOI: 10.56781/ijsret.2023.2.1.0028
Publication history:
Received on 05 November 2022; revised on 24 December 2022; accepted on 26 December 2022
Abstract:
Supervised classification is one of the tasks most frequently carried out by the intelligent systems. Supervised Machine Learning (SML) is the search for algorithms that reason from externally supplied instances to produce general hypotheses, which then make predictions about future instances. This paper; compares various supervised. Seven different machine learning algorithms were considered: Decision Table, Random Forest (RF) , Naïve Bayes (NB) , Support Vector Machine (SVM), Neural Networks (Perceptron), JRip and Decision Tree (J48)l. And also reviews various Supervised Machine Learning (ML) classification techniques with the aim of identifying the Best and Error free algorithm.
Keywords:
Machine Learning; Classifiers; Data Mining Techniques; Data Analysis; Learning Algorithms; Supervised Machine Learning
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0