Imbalance-XGBoost: leveraging weighted and focal losses for binary label-imbalanced classification with XGBoost.
Chen WangChengyuan DengSuzhen WangPublished in: Pattern Recognit. Lett. (2020)
Keyphrases
- class imbalance
- imbalanced datasets
- class labels
- binary classification problems
- imbalanced data
- pattern recognition
- class distribution
- image classification
- support vector
- classification accuracy
- training set
- classification algorithm
- multi class svm
- binary classifiers
- classification models
- machine learning methods
- decision trees
- binary classification
- feature extraction
- k nearest neighbour
- label information
- support vector machine
- decision rules
- text classification
- data sets
- svm classifier
- supervised learning
- highly skewed
- single class
- feature space
- minority class
- feature vectors
- cost sensitive learning
- active learning
- training samples
- classification scheme
- cost sensitive
- feature selection algorithms
- semi supervised