Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy.
Bartosz KrawczykMikel GalarLukasz JelenFrancisco HerreraPublished in: Appl. Soft Comput. (2016)
Keyphrases
- breast cancer
- breast cancer diagnosis
- mammogram images
- bladder cancer
- computer aided detection
- benign and malignant
- class imbalance
- diagnosis of breast cancer
- computer aided diagnosis
- cancer datasets
- early detection
- classification accuracy
- logistic regression
- microcalcification clusters
- breast tissue
- breast cancer patients
- lung nodules
- survival analysis
- feature selection
- decision trees
- cost sensitive
- active learning
- support vector
- cad systems
- outcome prediction
- feature extraction
- machine learning
- early detection of breast cancer
- class distribution