Network Flow Classification Based on Active Learning

GU Ming-yu

Chinese

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Network Flow Classification Based on Active Learning

更新时间：2026-09-04

- Network Flow Classification Based on Active Learning
- Vol. 28, Issue 9, Pages: 173-175(2011)
- 作者机构：
  
  安顺职业技术学院机构,贵州,安顺,561000
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2011
- 稿件说明：
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顾名宇. 基于主动学习方法的网络流分类研究[J]. 微电子学与计算机, 2011, 28(9): 173-175.

GU Ming-yu. Network Flow Classification Based on Active Learning[J]. 2011, 28(9): 173-175.
顾名宇. 基于主动学习方法的网络流分类研究[J]. 微电子学与计算机, 2011, 28(9): 173-175. DOI：

GU Ming-yu. Network Flow Classification Based on Active Learning[J]. 2011, 28(9): 173-175. DOI：

摘要

提出了一种基于主动学习方法的网络流分类方法

采用主动学习技术提取少量高质量的训练样本进行建模.并提出了一种基于轮盘赌选择的样本筛选方法

能够有效避免已有主动学习方法中的早熟收敛现象.实验结果表明

其相对于已有的流识别方法

能够在仅依赖少量高质量训练样本的前提下

保证较高的识别正确率

更适用于现实网络环境.

Abstract

This paper introduces an active learning method to select the most qualified data for training and propose a roulette wheel selection method.The experimental results demonstrate that the proposed method is able to guarantee high identification accuracy by using a small quantity of high qualified data.Therefore

it is more suitable for the real network applications than the traditional ones.

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