Let Imbalance Have Nowhere to Hide: Class-Sensitive Feature Extraction for Imbalanced Traffic Classification.
Yu GuoGaopeng GouGang XiongMinghao JiangJunzheng ShiWei XiaPublished in: IJCNN (2021)
Keyphrases
- feature extraction
- imbalanced datasets
- class imbalance
- class labels
- pattern classification
- feature vectors
- pattern recognition
- support vector machine svm
- single class
- minority class
- feature space
- imbalanced data
- class distribution
- multi class problems
- feature selection
- image classification
- binary classification problems
- classification accuracy
- cost sensitive learning
- classification algorithm
- multiclass classification
- feature extraction and classification
- image processing
- feature set
- linear feature extraction
- multi class
- dimension reduction
- decision trees
- rare class
- extracted features
- discriminant analysis
- multiple classes
- preprocessing
- support vector machine
- feature representation
- classification error
- imbalanced class distribution
- nearest neighbour
- sampling methods
- multi class classification
- machine learning
- text classification
- training data
- target class
- extracting features
- high dimensionality
- class imbalanced
- class specific
- cost sensitive
- classification method
- active learning
- training set