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A Review of the Principles and Applications of Mainstream Classification Algorithms: From Logistic Regression to Neural Networks

Year: 2026

Type: article

Abstract: This article illustrates four mainstream classification algorithms: logistic regression systematically, K-nearest neighbors (KNN), decision trees, and neural networks. Analyzed the mathematical principles, core calculation formulas, and basic achieving methods of each of these four kinds of algorithms; From the perspective of practical application scenes, analyze the applicability and obvious limitations of these algorithms when facing different data. This study provides a systematic proposal for the theoretical understanding and practical application of classification models in engineering and daily life.

Source: Frontiers in Computing and Intelligent Systems

DOI: 10.54097/3esa7m26

Author: Xinyang Zhao

Institution: Minzu University of China

Language: English

Topic: Data Mining and Machine Learning Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W7225179211

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