On the development of conjunctival hyperemia computer-assisted diagnosis tools: Influence of feature selection and class imbalance in automatic gradings.
María Luisa Sánchez BreaNoelia Barreira-RodríguezNoelia Sánchez-MaroñoAntonio Mosquera GonzálezCarlos García-ResúaMaría Jesús Giráldez FernándezPublished in: Artif. Intell. Medicine (2016)
Keyphrases
- class imbalance
- computer assisted diagnosis
- feature selection
- multispectral
- class distribution
- high dimensionality
- software defect prediction
- cost sensitive
- blood vessels
- active learning
- imbalanced datasets
- cost sensitive learning
- sampling methods
- feature space
- imbalanced data
- text classification
- concept drift
- feature selection algorithms
- machine learning
- decision trees
- minority class
- feature ranking
- training data
- data analysis
- neural network
- pairwise
- image data
- classification accuracy