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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 8
2398-2403

Logistic regression algorithm based on rotating granulation

Kong Liru1
Chen Yuming1
Fu Xingyu1
Jiang Hailiang1
Xu Jincheng2
1. College of Computer & Information Engineering, Xiamen University of Technology, Xiamen Fujian 361024, China
2. Xiamen Wanyin Intelligent Technology Co. , Ltd. , Xiamen Fujian 361024, China
DOI: 10.19734/j.issn.1001-3695.2023.11.0578

Abstract

LR serves as a generalized linear classifier for binary classification in supervised learning, exhibiting characteristics of simplicity in structure, strong interpretability, and effective fitting when dealing with linear data. However, its classification performance becomes limited when confronted with high-dimensional, uncertain, and linearly inseparable data. To address the inherent limitations of logistic regression, this paper introduced the theory of granular computing and proposed a novel logistic regression model called rotating granular logistic regression(RGLR). This paper introduced the theory of rotating granulation, where different angles of rotation were applied to pairs of features forming a plane coordinate system. This process constructed rotating granules by rotating pairs of features at various angles on the plane coordinate system, and granulated to form rotating granule vectors on multiple plane coordinate systems. This paper further defined the size, measurement, and operational rules of granules, and proposed a loss function for rotating granular logistic regression. The optimized solution of the rotating granular logistic regression was obtained by solving the value of the loss function. Finally, experiments are conducted using multiple UCI datasets, and the results compared across various evaluation metrics, indicate the effectiveness of the rotating granular logistic regression model.

Foundation Support

国家自然科学基金资助项目(61976183)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0578
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 8
Section: Algorithm Research & Explore
Pages: 2398-2403
Serial Number: 1001-3695(2024)08-021-2398-06

Publish History

[2024-02-23] Accepted Paper
[2024-08-05] Printed Article

Cite This Article

孔丽茹, 陈玉明, 傅兴宇, 等. 基于旋转粒化的逻辑回归算法 [J]. 计算机应用研究, 2024, 41 (8): 2398-2403. (Kong Liru, Chen Yuming, Fu Xingyu, et al. Logistic regression algorithm based on rotating granulation [J]. Application Research of Computers, 2024, 41 (8): 2398-2403. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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