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About It C Synopsis
This document presents a synopsis of internet traffic classification. It discusses challenges in traditional traffic classification techniques which typically achieve only 50-70% accuracy. The objectives are to develop a more accurate lightweight model for real-time classification using deep learning techniques. The methodology will involve data pre-processing steps like normalization, missing value imputation and feature selection, followed by classification using algorithms like Naive Bayes, Support Vector Machine (SVM) and Convolutional Neural Network (CNN). Literature on existing approaches is surveyed and challenges of traditional methods like PCA, Naive Bayes and SVM are outlined to motivate the proposed solution.
Detailed Information
Author: | ['UJJWAL KUMAR'] |
---|---|
Publication Year: | 2019 |
Pages: | 11 |
Language: | English |
Format: | |
Price: | FREE |
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