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

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.