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Machine Learning Algorithm for Classification

Journal of physics. Conference series, 2021-08, Vol.1994 (1), p.12016 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2021. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1994/1/012016

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  • Title:
    Machine Learning Algorithm for Classification
  • Author: Tan, Haoyuan
  • Subjects: Algorithms ; Classification ; Classifiers ; Hierarchies ; Machine learning
  • Is Part Of: Journal of physics. Conference series, 2021-08, Vol.1994 (1), p.12016
  • Description: Abstract Recently, machine learning methods have a good performance in the field of classification tasks. Summarizing and comparing the performances of different classifiers in the application of their specific classification tasks has a reference significance. In this paper, five classical machine learning classifiers, including GMM, Random Forest, SVM, XGBoost, and Naive Bayes, are compared to show their computing characteristics. The advantages and disadvantages are analysed in this paper. Based on the different datasets, namely different specific classification tasks, the different classifiers perform similarly. However, the SVM-based classifier has the lowest accuracy while processing the text data to apply the text classification task. This result shows that if the classification task is difficult, the accuracy would not be high. This research summarizes the performances of different machine learning methods in the application of specific classification tasks. And this research has a reference significance for the machine learning-based classifiers.
  • Publisher: Bristol: IOP Publishing
  • Language: English
  • Identifier: ISSN: 1742-6588
    EISSN: 1742-6596
    DOI: 10.1088/1742-6596/1994/1/012016
  • Source: IOP Publishing Free Content
    IOPscience (Open Access)
    GFMER Free Medical Journals
    ProQuest Central
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