Improving SMOTE with Fuzzy Rough Prototype Selection to Detect Noise in Imbalanced Classification Data.
Nele VerbiestEnislay RamentolChris CornelisFrancisco HerreraPublished in: IBERAMIA (2012)
Keyphrases
- prototype selection
- original data
- data sets
- noisy data
- pattern recognition
- machine learning
- high dimensional data
- training samples
- selection algorithm
- training data
- image classification
- text classification
- support vector machine
- active learning
- search algorithm
- class distribution
- training dataset
- nearest neighbor classifier
- imbalanced datasets