C4.5: programs for machine learning
C4.5: programs for machine learning
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Chi2: Feature Selection and Discretization of Numeric Attributes
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
Consistency-based search in feature selection
Artificial Intelligence
Transport layer identification of P2P traffic
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
An Extended Chi2 Algorithm for Discretization of Real Value Attributes
IEEE Transactions on Knowledge and Data Engineering
Toward Integrating Feature Selection Algorithms for Classification and Clustering
IEEE Transactions on Knowledge and Data Engineering
Internet traffic classification using bayesian analysis techniques
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
ACAS: automated construction of application signatures
Proceedings of the 2005 ACM SIGCOMM workshop on Mining network data
Traffic classification using clustering algorithms
Proceedings of the 2006 SIGCOMM workshop on Mining network data
ACM SIGCOMM Computer Communication Review
Data Mining
Identifying and discriminating between web and peer-to-peer traffic in the network core
Proceedings of the 16th international conference on World Wide Web
Offline/realtime traffic classification using semi-supervised learning
Performance Evaluation
Internet traffic classification demystified: myths, caveats, and the best practices
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
An SVM-based machine learning method for accurate internet traffic classification
Information Systems Frontiers
ASTUTE: detecting a different class of traffic anomalies
Proceedings of the ACM SIGCOMM 2010 conference
IEEE Transactions on Pattern Analysis and Machine Intelligence
NeTraMark: a network traffic classification benchmark
ACM SIGCOMM Computer Communication Review
Temporal Data Clustering via Weighted Clustering Ensemble with Different Representations
IEEE Transactions on Knowledge and Data Engineering
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
IEEE Transactions on Knowledge and Data Engineering
Feature selection strategy in text classification
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Toward the accurate identification of network applications
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
Traffic classification using a statistical approach
PAM'05 Proceedings of the 6th international conference on Passive and Active Network Measurement
IEEE Transactions on Knowledge and Data Engineering
Multilinear Discriminant Analysis for Face Recognition
IEEE Transactions on Image Processing
Bayesian Neural Networks for Internet Traffic Classification
IEEE Transactions on Neural Networks
Issues and future directions in traffic classification
IEEE Network: The Magazine of Global Internetworking
Review: A survey of network flow applications
Journal of Network and Computer Applications
A measurement-based study on the correlations of inter-domain Internet application flows
Computer Networks: The International Journal of Computer and Telecommunications Networking
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There is significant interest in the network management and industrial security community about the need to identify the ''best'' and most relevant features for network traffic in order to properly characterize user behaviour and predict future traffic. The ability to eliminate redundant features is an important Machine Learning (ML) task because it helps to identify the best features in order to improve the classification accuracy as well as to reduce the computational complexity related to the construction of the classifier. In practice, feature selection (FS) techniques can be used as a preprocessing step to eliminate irrelevant features and as a knowledge discovery tool to reveal the ''best'' features in many soft computing applications. In this paper, we investigate the advantages and disadvantages of such FS techniques with new proposed metrics (namely goodness, stability and similarity). We continue our efforts toward developing an integrated FS technique that is built on the key strengths of existing FS techniques. A novel way is proposed to identify efficiently and accurately the ''best'' features by first combining the results of some well-known FS techniques to find consistent features, and then use the proposed concept of support to select a smallest set of features and cover data optimality. The empirical study over ten high-dimensional network traffic data sets demonstrates significant gain in accuracy and improved run-time performance of a classifier compared to individual results produced by some well-known FS techniques.