Aug 15, 2021 · CMSVM adopts a multi-class SVM algorithm with active learning which dynamically assigns a weight for applications.
CMSVM adopts a multi-class SVM algorithm with active learning which dynamically assigns a weight for applications. We examine the classification accuracy and ...
A new dataset balancing method named SD sampling based on the SMOTE algorithm, which divides the sample into two types that are easy and difficult to ...
CMSVM adopts a multi-class SVM algorithm with active learning which dynamically assigns a weight for applications. We examine the classification accuracy and ...
People also ask
Is SVM good for multi class classification?
Which strategy is commonly employed in a multi class classification problem using SVM?
What is SVM classification algorithm?
What are the methods of network traffic classification?
ABSTRACT: Currently, the network traffic classification has two important problems, which are low accuracy and high computation complexity.
This study investigates the applicability of an active form of ML, called Active Learning (AL), in NTC, and results show that AL can achieve high accuracy ...
Pardhan employed two machine learning algorithms SVM and ANN to classify network traffic into 7 classes: FTP, WWW, P2P, NetBIOS, DNS, Mail, and Telnet [7] .
Mar 8, 2022 · Dong, “Multi class SVM algorithm with active learning for network traffic classification,” Expert Syst. Appl., vol. 176, Aug. 2021,. Art. no ...
Jan 30, 2024 · This work introduces a methodology, termed MTEFU, leveraging a deep learning model-based multi-task learning algorithm, strategically designed to mitigate the ...
In this paper, authors propose a new active learning algorithm. The algorithm is mainly proposed for multi-class classification model based on support vector ...
Missing: traffic | Show results with:traffic