Reducing False Negative Intrusions Rates of Ensemble Machine Learning Model based on Imbalanced Multiclass Datasets.
Salim Qadir MohammedMohammed A. ElSheikh HusseinPublished in: J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. (2023)
Keyphrases
- multi class
- binary classification problems
- false negative
- machine learning
- false positives
- support vector machine
- feature selection
- binary classification
- base classifiers
- multiclass classification
- single class
- decision trees
- multiclass problems
- multi class classification
- false positive rate
- intrusion detection
- pairwise
- binary classifiers
- cost sensitive
- multi class problems
- learning algorithm
- machine learning algorithms
- training data
- machine learning methods
- object detection
- ensemble learning
- multi task
- data mining
- multiple classes
- class imbalance
- text classification
- class distribution
- detection rate
- learning problems
- active learning
- learning tasks
- benchmark datasets
- perceptron algorithm
- supervised learning
- ensemble methods
- knn
- ensemble classifier
- svm classifier
- naive bayes
- anomaly detection
- semi supervised learning