Focal Loss Improves Performance of High-Sensitivity C-Reactive Protein Imbalanced Classification.
Ryan SledzikMahdieh ZabihimayvanPublished in: CBMS (2022)
Keyphrases
- high sensitivity
- classification accuracy
- training set
- machine learning
- optical fiber
- class imbalance
- pattern classification
- pattern recognition
- feature extraction
- feature vectors
- feature space
- image classification
- feature selection
- decision trees
- data sets
- single class
- cost sensitive
- classification method
- training samples
- machine learning methods
- classification algorithm
- roc curve
- class labels
- imbalanced data
- protein function
- text classification
- imbalanced data sets
- support vector