Mathematical Validation of Proposed Machine Learning Classifier for Heterogeneous Traffic and Anomaly Detection

Mathematical Validation of Proposed Machine Learning Classifier for Heterogeneous Traffic and Anomaly Detection

The modeling of an efficient classifier is a fundamental issue in automatic training involving a large volume of representative data. Hence, automatic classification is a major task that entails the use of training methods capable of assigning classes to data objects by using the input activities pr...

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Bibliographic Details
Main Authors: Azidine Guezzaz, Younes Asimi, Mourade Azrour, Ahmed Asimi
Format: Article
Language:English
Published: Tsinghua University Press 2021-03-01
Series:Big Data Mining and Analytics
Subjects:
anomaly detection
heterogeneous traffic
preprocessing
machine learning
training
classification
Online Access:https://www.sciopen.com/article/10.26599/BDMA.2020.9020019
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https://www.sciopen.com/article/10.26599/BDMA.2020.9020019

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