A dual-stage deep learning model based on a sparse autoencoder and layered deep classifier for intrusion detection with imbalanced data.
Omar Al-HarbiAhmed HamedPublished in: Int. J. Sens. Networks (2024)
Keyphrases
- deep learning
- intrusion detection
- imbalanced data
- restricted boltzmann machine
- support vector machine
- feature selection
- ensemble classifier
- svm classifier
- anomaly detection
- machine learning
- unsupervised learning
- classification models
- decision trees
- class distribution
- minority class
- ensemble learning
- decision boundary
- data mining
- random forest
- training set
- training data
- mental models
- weakly supervised
- support vector
- ensemble methods
- training samples
- feature space
- data mining techniques
- feature set
- multi class
- learning algorithm
- class imbalance
- class labels
- classification error
- classification algorithm
- base classifiers
- input image
- feature vectors
- pairwise
- object recognition
- image segmentation