lib•erate, (n): a library for exposing (traffic-classification) rules and avoiding them efficiently.
Fangfan LiAbbas RazaghpanahArash Molavi KakhkiArian Akhavan NiakiDavid R. ChoffnesPhillipa GillAlan MislovePublished in: Internet Measurement Conference (2017)
Keyphrases
- training examples
- classification rules
- active learning
- genetic programming
- predictive accuracy
- decision trees
- rule sets
- ant miner
- association rules
- subgroup discovery
- associative classification
- nearest neighbor
- classification algorithm
- action rules
- real time
- human experts
- artificial intelligence
- rule discovery
- fuzzy rules
- prior knowledge
- decision tree algorithm
- associative classifiers