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Research status and future prospects of machine learning algorithm in big data analysis

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DOI: 10.23977/jnca.2021.060101 | Downloads: 1 | Views: 60

Author(s)

Haonan Wang 1

Affiliation(s)

1 Data Science Experiment Center of College of Science, Liaoning University of Engineering and Technology, Fuxin 123000, China

Corresponding Author

Haonan Wang

ABSTRACT

In the field of big data analysis, with the help of machine learning algorithm, the traditional mode of data analysis has been changed and the development of data processing and analysis has been promoted. This paper first explains the concepts of machine learning and big data analysis, then introduces the classic concepts and application concepts of three kinds of classical machine learning algorithms, namely naive Bayesian algorithm, K-means algorithm and SVM algorithm, and then discusses the application mode of machine learning algorithm in the emerging stage of big data environment, so as to enhance the value of big data processing. Finally, it looks forward to the big data processing The research trend of machine learning algorithm in this field is analyzed.

KEYWORDS

Big data, machine learning, naive Bayesian, k-means, SVM

CITE THIS PAPER

Haonan Wang. Research status and future prospects of machine learning algorithm in big data analysis. Journal of Network Computing and Applications (2021) 5: 1-5. DOI: http://dx.doi.org/10.23977/jnca.2021.060101

REFERENCES

[1] Ou huajie. Overview of machine learning algorithms under the background of big data [J]. China informatization, 2019(04): 50-51.
[2] He Qing, Li Ning, Luo Wenjuan, Shi Zhongzhi. Overview of machine learning algorithms under big data [J]. Pattern Recognition and Artificial Intelligence, 2014, 27(04): 327-336.
[3] Xu hongxue, sun Wanyou, du yingkui, Wang anqi. a summary of classical algorithms of machine learning and their applications [J]. Computer knowledge and technology, 2020, 16(33): 17-19.
[4] Ou Huajie. Overview of machine learning algorithms under the background of big data [J]. China Informatization, 2019(04): 50-51

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