An alternative to SVM Method for Data Classification

원문 초록

Support vector machine (SVM), is a popular kernel method for data classification that demonstrated its efficiency for a large range of practical applications. The method suffers, however, from some weaknesses including; time processing, risk of failure of the optimization process for high dimension cases, generalization to multi-classes, unbalanced classes, and dynamic classification. In this paper an alternative method is proposed having a similar performance, with a sensitive improvement of the aforementioned shortcomings. The new method is based on a minimum distance to optimal subspaces containing the mapped original classes.

함께 살펴볼 논문

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arXiv:2507.12292공통 태그 Classification공식 코드 · Papers with Code 등록 2025-07-16

Efficient Calisthenics Skills Classification through Foreground Instance Selection and Depth Estimation

arXiv:2507.09759공통 태그 Classification공식 코드 · Papers with Code 등록 2025-07-13

AI-Enhanced Pediatric Pneumonia Detection: A CNN-Based Approach Using Data Augmentation and Generative Adversarial Networks (GANs)

arXiv:2507.03421공통 태그 Classification공식 코드 · Papers with Code 등록 2025-07-04

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An alternative to SVM Method for Data Classification

원문 초록

함께 살펴볼 논문

Efficient Calisthenics Skills Classification through Foreground Instance Selection and Depth Estimation

AI-Enhanced Pediatric Pneumonia Detection: A CNN-Based Approach Using Data Augmentation and Generative Adversarial Networks (GANs)

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