Ensemble of classifiers based network intrusion detection system performance bound.
Nenekazi N. P. MkuzangweFulufhelo V. NelwamondoPublished in: ICSAI (2017)
Keyphrases
- ensemble learning
- ensemble classifier
- classifier ensemble
- multiple classifiers
- ensemble pruning
- training data
- majority voting
- training set
- pac bayes
- combining classifiers
- individual classifiers
- weighted voting
- feature selection
- class label noise
- final classification
- ensemble methods
- majority vote
- ensemble classification
- ensemble members
- accurate classifiers
- multiple classifier systems
- upper bound
- randomized trees
- concept drifting data streams
- decision tree classifiers
- trained classifiers
- linear classifiers
- imbalanced data
- lower bound
- base classifiers
- decision trees
- feature ranking
- support vector
- one class support vector machines
- weak learners
- bias variance decomposition
- machine learning algorithms
- neural network
- active learning
- classifier combination
- binary classification problems
- feature set
- machine learning methods
- random forest
- pruning method
- class labels
- machine learning
- rule induction algorithm
- text categorization
- weak classifiers
- generalization bounds
- learning algorithm
- generalization ability
- diversity measures
- roc curve
- classification algorithm
- worst case
- mining concept drifting data streams