FEAML: A Mobile Traffic Classification System with Feature Expansion and Autonomous Machine Learning.
Qing YangXiangyu KongYilei XiaoYue LinRui WenHeng QiPublished in: ICA3PP (5) (2023)
Keyphrases
- machine learning
- machine learning methods
- feature vectors
- decision trees
- pattern recognition
- machine learning algorithms
- support vector machine
- supervised classification
- supervised machine learning
- feature selection
- classification accuracy
- supervised learning
- text classification
- mobile devices
- computer vision
- data mining
- feature set
- automatic classification
- model selection
- discriminative features
- real time
- support vector
- unsupervised learning
- network traffic
- pattern classification
- machine learning approaches
- feature extraction
- neural network
- feature representation
- feature ranking
- classification models
- feature weights
- classification method
- class labels
- knowledge acquisition
- mobile phone
- image classification
- image features
- information extraction
- training set
- feature space
- data analysis